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Genes in human obesity loci are causal obesity genes in C. elegans

['Wenfan Ke', 'Department Of Biology', 'College Of Arts', 'Sciences', 'University Of Virginia', 'Charlottesville', 'Virginia', 'United States Of America', 'Jordan N. Reed', 'Department Of Biomedical Engineering']

Date: 2021-11

Obesity and its associated metabolic syndrome are a leading cause of morbidity and mortality. Given the disease’s heavy burden on patients and the healthcare system, there has been increased interest in identifying pharmacological targets for the treatment and prevention of obesity. Towards this end, genome-wide association studies (GWAS) have identified hundreds of human genetic variants associated with obesity. The next challenge is to experimentally define which of these variants are causally linked to obesity, and could therefore become targets for the treatment or prevention of obesity. Here we employ high-throughput in vivo RNAi screening to test for causality 293 C. elegans orthologs of human obesity-candidate genes reported in GWAS. We RNAi screened these 293 genes in C. elegans subject to two different feeding regimens: (1) regular diet, and (2) high-fructose diet, which we developed and present here as an invertebrate model of diet-induced obesity (DIO). We report 14 genes that promote obesity and 3 genes that prevent DIO when silenced in C. elegans. Further, we show that knock-down of the 3 DIO genes not only prevents excessive fat accumulation in primary and ectopic fat depots but also improves the health and extends the lifespan of C. elegans overconsuming fructose. Importantly, the direction of the association between expression variants in these loci and obesity in mice and humans matches the phenotypic outcome of the loss-of-function of the C. elegans ortholog genes, supporting the notion that some of these genes would be causally linked to obesity across phylogeny. Therefore, in addition to defining causality for several genes so far merely correlated with obesity, this study demonstrates the value of model systems compatible with in vivo high-throughput genetic screening to causally link GWAS gene candidates to human diseases.

Human GWAS have identified hundreds of genetic variants associated with human obesity. The genes being regulated by these variants at the protein or expression level represent potential anti-obesity targets. However, for the vast majority of these genes, it is unclear whether they cause obesity or are coincidentally associated with the disease. Here we use a high-throughput genetic screening strategy to test in vivo in Caenorhabditis elegans the potential causal role of human-obesity GWAS hits. Further, we combined the results of the genetic screen with analyses of mouse and human GWAS databases. As a result, we present 17 genes that promote or prevent C. elegans obesity, and the early onset of organismal deterioration and death associated with obesity. Further, the sign of the correlation between the expression levels of the human genes and their associated clinical traits matches, for the most part, the phenotypic effects of knocking down these genes in C. elegans, suggesting conserved causality and pharmacological potential for these genes.

Funding: M.C is funded by National Institutes of Health (DK118287) A.E.C. is funded by National Institutes of Health (GM122547) E.J.O'R. is funded by Pew Charitable Trusts (Biomedical Scholars Award), National Institutes of Health (DK087928), W. M. Keck Foundation, and Jeffress Trust Award The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. NIH (DK118287) supported the salaries of M.C. and J.N.R. NIH (T32 HL007284) supported the salary of J.N.R. NIH(GM122547) supported the salary of A.E.C. All other funders supported salaries of E.J.O’R., W.K., L.R.

In this study, we exploit a high-throughput in vivo obesity screen system to test for causality genes significantly associated with obesity in human GWAS. First, we identified 340 candidate genes from published GWAS and built a C. elegans RNAi library containing 293 worm orthologs of the human-obesity candidate genes. We used our previously developed screening pipeline [ 39 , 50 ] to perform an RNAi screen for genes whose inactivation alters the fat content of C. elegans fed a regular diet (RD). In this screen, we found 14 obesity genes (inactivation leads to obesity) and two lean genes (inactivation leads to leanness). We also established a C. elegans DIO model by feeding worms a high-fructose diet (HFrD). We show that worms fed a HFrD not only have higher fat content and body size, but also exhibit shortened health and lifespan. Using this DIO model, we identified three human genes whose C. elegans orthologs are DIO suppressors (inactivation prevents HFrD-induced obesity). Furthermore, we show that inactivation of the three DIO suppressors also ameliorates the detrimental effects of a HFrD on C. elegans health and lifespan. Altogether, this study provides a path to validate human GWAS obesity candidates in vivo in a high-throughput manner for future development of pharmacological interventions to reduce the burden of obesity.

As for diet-induced obesity (DIO), a high-glucose DIO model that shows both increased fat accumulation and shortening of lifespan has been previously described for C. elegans [ 46 , 47 ]. Less unanimous, though, are previous reports on the effect of fructose supplementation on the C. elegans diet. A diet supplemented with 50mg/mL or 100mg/mL of fructose was shown to reduce C. elegans healthspan and lifespan by Lodha et al [ 48 ] and Zheng et al [ 49 ], respectively. However, fructose at doses of 10 and 20mg/mL extended C. elegans’s lifespan. Further, the obesogenic effect of dietary supplementation of fructose has not been previously demonstrated in C. elegans.

Genetic screening in Caenorhabditis elegans has effectively identified drug targets for human diseases ranging from depression (e.g., Prozac) [ 36 ] to metabolic disease (e.g., metformin) [ 37 ]. As the first, and only, model organism enabling whole-genome systemic RNA interference (RNAi) in vivo through feeding, C. elegans is an ideal system for high throughput identification of gene function [ 38 , 39 ]. C. elegans is evolutionarily distant from humans. Nevertheless, core lipid, sugar, and protein metabolism pathways are conserved between the two species [ 40 ]. Regulators such as TOR kinase and AMPK, and transcription factors such as Sterol response element binding protein (SREBP), Peroxisome proliferator-activated receptor gamma (PPARγ), and Transcription Factor EB (TFEB), similarly control metabolic genes and cellular responses to nutrients in both organisms. Loss of function of such regulators causes similar metabolic dysregulation, such as obesity or resistance to it, in worms and mammalian systems [ 41 – 45 ]. Moreover, in terms of identifying druggable targets, an obesity candidate gene identified in human GWAS whose ortholog is demonstrated to contribute to obesity in C. elegans is more likely to be a robust anti-obesity target across human populations.

On the other side, even when we share an obesogenic environment not everyone becomes obese, implying that a sizable portion of the variation in weight among adults would be due to genetic factors. Further, protein-coding genes whose sole inactivation is sufficient to prevent, ameliorate, or revert obesity equate to promising druggable targets. Genome-wide association studies (GWAS) are one of the most promising approaches to identify these gene targets because GWAS search for genetic variants associated with obesity in human populations living in their daily environments (as opposed to animal models reared in controlled conditions). Once identified, the genetic variants can be mapped to genes that may increase or decrease the likelihood of obesity occurrence [ 21 ]. Currently, there are over 90 GWAS, which associate 2,537 SNPs with different obesity metrics including body mass index (BMI), waist to hip ratio (WHR), WHR adjusted for BMI, body fat distribution, and/or body fat percentage [ 22 ]. Almost 90% of these variants are found in non-coding regions of the genome [ 23 ]; hence, very few variants have been mapped to genes. Further, even for those variants that can be reliably mapped to genes, after two decades, only a handful have been causally linked to the disease [ 24 – 34 ]. A major barrier to distinguish statistical association from causal association for the hundreds of loci associated with obesity or diet-induced obesity (DIO) is the lack of in vivo systems that enable experimental testing at a reasonable throughput and cost [ 35 ].

On one side, the rapid increase in the prevalence of obesity observed in recent decades has been attributed to an “obesogenic environment, which offers ready access to high-calorie foods but limits opportunities for physical activity” ( www.CDC.gov ). Studies aimed to elucidate the role of carbohydrates in obesity suggested that high sugar consumption could be the main factor behind the alarming increase in the incidence of obesity and metabolic syndrome. More specifically, increased fructose intake from high-fructose corn syrup was found to be highly correlated with the increase in the incidence of obesity observed in the past 40 years [ 12 – 14 ]. Compared to glucose, fructose consumption is more effective at promoting excessive visceral fat accumulation [ 15 ] [ 16 ]. In line with this, in both humans and rodents, high-fructose diets (HFrD) are functionally linked to the general metabolic dysregulation associated with obesity, also known as metabolic syndrome [ 17 – 20 ].

Obesity is a major risk factor for serious comorbidities including cardiovascular disease (CVD), type 2 diabetes, hypertension, stroke, neurodegenerative disease, and certain cancers [ 1 , 2 ]. In the past decade, obesity-derived comorbidities caused more than 4 million deaths per year and cost an average of 4 years of life lost worldwide [ 3 – 5 ]. The increased prevalence of obesity and extreme obesity could lead to a global average reduction in life expectancy in the next decade [ 6 , 7 ]. Therefore, there is an urgent need to improve the toolset to reduce the burden of obesity [ 8 – 10 ]. Identifying more effective points of intervention to treat obesity is difficult because obesity is a complex disease influenced by various interacting factors including socioeconomic status, physical activity, eating habits, microbiota, and multiple genes acting in multiple tissues [ 11 ].

Throughout this figure: Error bars = S.E.M. N = numbers of independent biological replicates. Unless specified, unpaired nonparametric t-tests were used to assess the significance. *p≤ 0.05, **p≤0.01, ***p≤0.001 and ****p≤0.0001. ( A - D ) Comparison of the lifespan of worms fed HFrD while treated with empty RNAi vector control (EV) or RNAi against the DIO suppressors: ( A) Y71H10B.1, ( B ) let-767, and ( C ) pho-1. N = 1 is depicted in this figure. N = 3 is shown in S3 Table ( D ) Motor capacity of worms fed RD or HFrD and treated with RNAi against the DIO suppressors measured as bends/second after flooding as described in Materials and Methods section. N = 3. ( E ) Spontaneous displacement velocity on the surface of bacteria-free NGM plates of worms fed RD or HFrD and treated with RNAi against the DIO suppressors. N = 3.

DIO reduces C. elegans healthspan and lifespan ( Fig 4I , 4J , 4K and 4L ). Therefore, we next assessed whether the suppressors of DIO would also suppress the shortening of lifespan caused by a HFrD. For the DIO-suppresor genes that do not cause a developmental delay (pho-1 and Y71H10B.1), the RNAi treatment was started on L1 larvae. For the gene causing developmental delay (let-767), RNAi was started at the L4 stage. Survival over time was assessed in three independent biological replicates (summarized in S3 Table ). Only lifespan reduction or extension with p<0.05 (Gehan-Breslow-Wilcoxon test) in all three independent replicates was considered significant. We found that RNAi against pho-1, let-767, and Y71H10B.1 partially suppressed the short lifespan associated with DIO ( Fig 7A , 7B and 7C and S3 Table ). On the other hand, knockdown of the same genes did not alter C. elegans’s lifespan significantly when animals are fed a regular diet ( S3 Table ). To examine if knockdown of the genes that reduce body fat also restores C. elegans health, we evaluated the behavioral response to flooding (swimming response) and spontaneous locomotion of animals with knockdown of the three DIO-suppressor genes (let-767, Y71H10B.1, and pho-1). We found that knockdown of Y71H10B.1 ameliorated the swimming response ( Fig 7D ), and that knockdown of all of these genes ameliorated spontaneous locomotion in animals fed HFrD ( Fig 7E ). These findings support the notion that reducing body fat content can reduce the health and lifespan burdens associated with obesity in C. elegans, and provide evidence of the potential value of these genes as pharmaceutical targets.

Throughout this figure: Scale bars = 20μm. Error bars = S.E.M. N = numbers of independent biological replicates. Unless specified, ratio t-tests were used to assess the significance. *p≤ 0.05, **p≤0.01, ***p≤0.001 and ****p≤0.0001. Tissue-specific lipid droplet (LD) reporters strains XD3971, XD1875 and XD2458 express Drosophila PLIN1::GFP in the intestine (daf-22 promoter), muscle (unc-54 promoter), and hypodermis (Y37A1B.5 promoter), respectively. LD size and abundance assessments as described in the Materials and Methods section. Each data point represents the GFP measurement of a 0.003mm 2 square area of the tissue. I: intestine, M: muscle, H: hypodermis. N = 3.Unpaired nonparametric t-tests were used to assess the significance. ( A-A’ ) LD size in the C. elegans intestine is reduced in Y71H10B.1, let-767, and pho-1 RNAi-treated animals fed regular or HFrD diet. ( A & D ) LD abundance in the intestine (I) of worms fed regular diet (RD) is reduced in animals treated with RNAi against Y71H10B.1, but not let-767. pho-1 increases the LD pool in the intestine. N = 3. ( B & D ) Similar to the intestine, LD abundance in the muscles (M) of C. elegans fed regular diet (RD) is reduced in Y71H10B.1, but not in let-767 RNAi-treated animals. pho-1 RNAi increases the LD pool in the intestine. N = 3. ( C & D ) LD abundance in the hypodermis (H) of C. elegans fed regular diet (RD) is reduced in animals treated with RNAi against Y71H10B.1, let-767, and pho-1. N = 3. ( A & E ) LD abundance in the intestine of worms fed a high-fructose diet (HFrD) is reduced by RNAi treatment against Y71H10B.1 and let-767, whereas RNAi against pho-1 increases the LD pool in the intestine. N = 3. ( B & E ) LD abundance in the muscles of C. elegans fed HFrD is reduced in animals treated with RNAi against Y71H10B.1, but not let-767 or pho-1. ( C & E ) LD abundance in the hypodermis of C. elegans fed HFrD is reduced in animals treated with RNAi against Y71H10B.1, let-767, and pho-1. N = 3.

We already described above that expression of the human ortholog of Y71H10B.1, NT5C2, positively correlates with waist-to-hip ratio and circulating triglycerides ( Fig 3B ), which is in line with knockdown of Y71H10B.1 in C. elegans promoting leanness in animals fed a regular or high-fructose diet. In a more difficult to interpret case, the expression of the human ortholog of let-767, HSD17B12, although negatively associated with BMI, is positively associated with free fatty acids, indicating that reduced expression of HSD17B12 is associated with obesity but also with improved lipid metabolism. Suggesting a similarly complicated role, expression of the mouse ortholog, Hsd17b12, is both negatively (e.g., with % body fat) and positively (e.g., glucose and circulating triglycerides) associated with markers of metabolic health ( Fig 3B ). Therefore, future studies would be necessary to define whether the role of let-767 in promoting obesity is conserved in mammals. Finally, using the METSIM cohort, we found that the expression of the human ortholog of pho-1, ACP2, positively correlates with body weight and total triglycerides ( S4 Fig ), which is in line with our observations showing that knockdown of C. elegans’s pho-1 prevents diet-induced obesity.

Throughout this figure: Scale bars = 200μm. Error bars = S.E.M. N = number of independent biological replicates. Statistical significance was assessed via ratio t-test, *p≤ 0.05, **p≤0.01, ***p≤0.001 and ****p≤0.0001. ( A ) Representative images of the body fat content and distribution observed in worms fed HFrD while treated with RNAi against the following genes: Left = pho-1 and Y71H10B.1 RNAi treatment from the L1 stage. Right = let-767 RNAi treatment from the L4 stage. ( B & D ) ORO signal intensity in worms treated with RNAi as shown in panel A. Each data point represents the ORO intensity values in each worm normalized to the mean ORO intensity value of the EV control. N = 3. ( C & E ) Body size of worms treated with RNAi as shown in panel A. Each data point represents the measurement of a worm. Individual body size values were normalized to the mean value of the EV control. N = 3.

From the primary DIO screen, we identified eight high-confidence DIO-suppressor genes. Using the same rationale and approach described above ( S1A Fig ), we retested the eight genes in 6cm NGM plates. We confirmed the DIO-suppressor phenotype for five out of the eight primary hits. From the five DIO suppressors, pho-1 (human gene ACP2) and Y71H10B.1 had no detrimental effects on development ( Fig 5A , 5B and 5C ). However, the other three genes–rpt-5, hsp-4, and let-767 –caused severe developmental delay ( S3C Fig and S1 Table ). Starting the RNAi treatments against these genes at the L4 stage, showed that post-developmental inactivation of rpt-5 and hsp-4 did not prevent DIO ( S3D Fig ). On the other hand, L4-knockdown of let-767 reduced body fat content and body size in worms fed HFrD ( Fig 5A , 5D and 5E ), suggesting that let-767 would independently modulate fat metabolism and development. Importantly, let-767 and Y71H10B.1 were also lean hits in the regular diet screen described above ( Fig 2 ), suggesting a generic function for these genes in promoting fat accumulation. By contrast, pho-1 knockdown only prevented obesity in worms fed a HFrD, suggesting a specific function in DIO. Together, we identified and confirmed three genes–pho-1, let-767, and Y71H10B.1 –whose knockdown prevented the development of obesity in animals fed excessive sugar.

We tested the 293 C. elegans orthologs of the human obesity GWAS candidate genes for DIO causality by screening for RNAi treatments that led to reduced or no obesity even when worms were fed excessive fructose. The screening set up for this DIO screen is as described for the regular-diet screen ( S1A Fig ) except that 10mg/mL of fructose (1% fructose) were supplemented to the Nematode growth media plates. After knocking down the 293 C. elegans genes, we observed two phenotypic classes: (1) Wild type: after RNAi treatment, worms in these populations showed the larger quantity and broader distribution of ORO signal that characterizes DIO; this was the expected ORO phenotype because the worms were feeding excessive levels of fructose; and (2) DIO suppressors: ≥50% of worms in an RNAi treatment showed reduced fat content when compared to EV controls, suggesting that the gene normally contributes to HFrD-driven obesity in C. elegans. The RNAi treatments that showed a DIO-suppressor phenotype consistently in 3 or more independent biological replicates were selected for further validation.

Obesity is defined by the World Health Organization as abnormal or excessive fat accumulation that presents a higher risk of debilitating co-morbidities and death [ 85 – 87 ]. In C. elegans, excessive fat accumulation is not always associated with deleterious co-morbidities in health. For instance, mutation of the C. elegans insulin receptor (IR) daf-2 leads to excessive fat accumulation [ 67 ]. However, daf-2 mutant animals are resistant to age-related decline and long lived [ 88 – 90 ]. Consistently, even though GH receptor knockout (GHRKO) mice have increased fat mass and decreased lean mass, they show improved insulin sensitivity and are long lived [ 91 ]. Therefore, to establish an informative model of DIO in C. elegans, it is critical to test whether the increase in fat levels correlates with detrimental effects on health. To this end, we first evaluated the effect of HFrD on overall survival by comparing the lifespan of HFrD-fed worms to the lifespan of the RD-fed worms. HFrD reduced the median lifespan of C. elegans by 69% (Gehan-Breslow-Wilcoxon test), with a 31.49 average Hazard Ratio (Mantel-Haenszel test) ( Fig 4I and S2 Table ). Next, we conducted healthspan assays as described previously [ 90 ]. In the case of locomotory capacity, we found a significant reduction in body bending rate and average velocity in 3-day old worms fed HFrD when compared to worms of the same age fed RD ( Fig 4J and 4K ). In C. elegans, locomotion defects including impaired body bending and reduced velocity can be caused by reduced proteostasis [ 92 ], and in humans, obesity is strongly associated with neurodegenerative diseases characterized by uncurbed protein aggregation [ 93 – 95 ]. Therefore, we hypothesized that high fructose levels in the C. elegans diet may reduce proteostasis, which could in turn lead to an earlier onset of locomotion defects. As previously reported, C. elegans constitutively expressing a toxic form of the human Aβ amyloid (strain GRU102) show an earlier onset of locomotory impairment than worms expressing a non-toxic form of the human Aβ amyloid (strain GRU101), and this reduced locomotory capacity is due to reduced proteostasis in the neuro-locomotory system [ 92 , 96 ]. To test the hypothesis that reduced proteostasis would contribute to the reduced locomotory capacity observed in worms fed HFrD, we fed a regular diet or HFrD to the GRU101 and GRU102 worms. We conducted a “food race” assay as previously described [ 97 ]. Briefly, we placed fifty 3-day old adult worms from each condition (GRU102 ± fructose and GRU101 ± fructose) at one end of a 10cm NGM plate. To start the assay, 25μl of E. coli suspension (OD 600nm = 20) were placed on the plates on the opposite side of the worms. After 1h, the number of the worms fully or partially within the borders of the mini bacterial lawn was counted. We consistently found fewer worms expressing toxic Aβ than worms expressing the non-toxic Aβ in the lawns ( Fig 4L ), confirming the published detrimental effect of increased protein aggregation on C. elegans locomotion. We also observed HFrD to be sufficient to impair C. elegans locomotion ( Fig 4L ). Tellingly, the HFrD-derived impairment was not additive to the expression of toxic Aβ ( Fig 4L ), suggesting the possibility that HFrD and Aβ overexpression may share a common mechanism of toxicity, which we hypothesize might be reduced proteostasis. Altogether, we found that overconsumption of fructose in C. elegans evokes several of the hallmarks of human obesity including elevated body fat content in primary and ectopic fat storage tissue subcellularly characterized by increases in the number and size of the LDs, in conjunction with reduced health and lifespan.

Adipose is the main fat storage tissue in humans, and adipocytes with increased lipid droplet (LD) number and size are cellular hallmarks of obesity [ 76 ]. In C. elegans, there are no specialized adipose cells. The primary triglyceride depots are found in the worm’s intestinal cells and are contained in LDs sized between 0.5–1.5 μm [ 77 , 78 ]. To define whether C. elegans fed a HFrD would show changes in the abundance and/or size of the LDs, we used a LD reporter consisting of Drosophila PLIN1::GFP driven by the intestine-specific promoter daf-22 [ 79 , 80 ]. In agreement with the mammalian subcellular hallmarks of obesity, we observed an increase in both the overall intensity ( Fig 4D and 4E ) and the size ( Fig 4F ) of the LDs in the intestine of HFrD-fed worms. Another common feature of human obesity is the increase in ectopic fat stores (fat outside the primary fat storage tissues) [ 81 ], with excess ectopic fat being associated with worse health outcomes [ 82 ]. Although C. elegans does not have a dedicated adipose tissue, fat beyond the intestine is observed in mutants with metabolic dysregulation such as the mTORC2-component mutant rict-1, in which fat is additionally observed in muscle and hypodermis [ 83 , 84 ]. To further characterize the distribution of the fat stores in the HFrD worms, we used the Drosophila PLIN1::GFP construct driven by the unc-54 promoter to express it in the muscle, or driven by the Y37A1B.5 promoter to express it in the hypodermis [ 79 , 80 ]. We again observed a significant increase in the LD intensity ( Fig 4D , 4G and 4H ) but no change in LD size ( S3A and S3B Fig ), in the muscle and hypodermis of worms fed HFrD. These observations suggest excess fat is stored in primary and ectopic tissues in C. elegans, comparable at a subcellular level to what is observed in visceral and ectopic fat depots in humans with obesity.

Throughout this figure: Error bars = S.E.M. N = numbers of independent biological replicates. Unless specified, unpaired nonparametric t-tests were used to assess the significance. *p≤ 0.05, **p≤0.01, ***p≤0.001 and ****p≤0.0001. ( A ) Representative images of the body fat content and distribution in worms fed regular diet (RD) or high-fructose diet (HFrD) from the L1 stage, and stained with ORO when day-1 adults. Scale bar = 200μm. ( B ) Quantification of ORO intensity in worms for fed RD or HFrD as represented in panel A. Each data point represents the measurement of a single worm. N = 3. ( C ) Body size quantification of worms fed RD or HFrD. Each data point represents the ImageJ-measured length of a single worm. N = 3. ( D ) Tissue-specific LD phenotype in worms fed RD (top) or HFrD (bottom). Description of the transgenic reporters is depicted in the panel. Scale bar = 20μm. ( E ) Mean GFP intensity of intestinal LDs per worm, in worms fed RD or HFrD as represented in D. Each data point represents the measurement of a 0.004mm 2 intestinal square area of a worm. N = 3. ( F ) Mean intestinal LD size in worms fed RD or HFrD. Each data point represents the size measurement of an individual LD randomly selected from ≥10 worms from each independent biological replicate. N = 3. ( G ) Mean GFP intensity of muscle LDs in worms fed RD or HFrD, as shown in D. Each data point represents the measurement of a 0.003mm 2 square area of muscle behind the pharynx of a worm. N = 3. ( H ) Mean GFP intensity of hypodermal LDs in worms fed RD or HFrD, as shown in D. Each data point represents the measurement of a 0.003mm 2 square area of hypodermis behind the pharynx of a worm. N = 3. ( I ) Lifespan assessment of worms fed RD or HFrD. N = 1 is shown in this panel, N = 3 summarized in S2 Table . ( J ) Locomotory capacity measured as body bends per second in worms fed RD or HFrD. N = 3. ( K ) Locomotory capacity measured as displacement velocity in worms fed RD or HFrD while on the surface of bacteria-free NGM plates. N = 3. ( L ) Neurolocomotory and sensorial capacity measured in a food race assay as described in Materials and Methods section. Genotypes: GRU101 = worms with pan-neuronal expression of non-toxic human Aβ, and GRU102 = worms with pan-neuronal expression of toxic human Aβ. N = 3.

Excessive dietary intake of fructose has been suggested to be a major driver of the obesity epidemic [ 72 , 73 ], as fructose is the most common additive in industrialized foods [ 74 ]. To test the potential contribution of the human GWAS obesity candidates in the development of DIO we established a fructose-driven C. elegans model of DIO. We named high-fructose diet (HFrD) the dietary regimen in which worms are grown from the L1 stage in plates of Nematode growth media (NGM) supplemented with 10mg/mL of fructose (1% fructose). We observed that at the adult stage, worms fed a HFrD show a significant increase in body fat content compared to those fed a regular diet (RD) ( Fig 4A and 4B ). Further, worms fed the HFrD are also larger than worms fed RD ( Fig 4C ), which is similar to a previous report showing increased body size in worms fed excessive glucose [ 75 ].

Lastly, a gene variant can impact fat accumulation rather directly, because the gene is involved in fat metabolism or its regulation, or rather indirectly because the variant causes general sickness. We investigated this by defining to what extent a gene variant affects metabolic-specific or metabolic-related traits as opposed to unrelated disease traits. We queried the GWAS catalog for each human ortholog of the C. elegans hit genes. It is worth noting that the METSIM study has not yet been included in the GWAS catalog, therefore it was excluded from this analysis. Variants near KAT8, TCF7L2, DHX33, POLR1D, HSD17B12, NT5C2, and MTCH2 were significantly associated with BMI. Variants near GNL3, NOTCH4, ADAMTS9, and EIF6 were significantly associated with waist/hip ratio adjusted for BMI. ( S1 and S2 LocusPlots). We found 15 out of the 16 loci associated with any human disease traits (DHX33 is unassociated). Of these, 11 genes were associated with metabolic traits beyond obesity such as insulin resistance, fat distribution, and cardiovascular disease in human GWAS ( Fig 3C , black bars). Further, the variants linked to ADAMTS9, HSD17B12, TCF7L2, KAT8, NT5C2, and GLN3 seem to be mostly associated with metabolic phenotypes as opposed to non-metabolic disease traits ( Fig 3C , brown labels indicate genes with the largest proportion of metabolic traits), suggesting these genes may have a rather specific role in metabolic health. In summary, we found supportive evidence in mammalian systems of a role in obesity and metabolic syndrome for most of the orthologs of the genes that we causally linked to obesity in C. elegans.

To test the hypothesis that the C. elegans hit genes would have conserved causal roles in human obesity we performed similar analyses using the METSIM cohort. We found 16 human genes corresponding to 16 C. elegans gene hits in this dataset. However, on one hand, NOTCH4 and EYS are both orthologs of C. elegans glp-1, and on the other hand, puf-8 and fbf-2 are both orthologs of human PUM2. We calculated the degree of association between the expression in adipose tissue of the 16 human genes and clinical traits including body mass index (BMI) and waist-to-hip ratio (WHR). BMI was the most strongly associated trait ( Fig 3B ). Further, most human genes showed expression associations with BMI that were in the same direction as in C. elegans. Specifically, lower expression of PUM2, POLR1D, ADAMTS9, DHX33, NOTCH4, EYS, TCF7L2, and KAT8 correlates with increased BMI, which is comparable to the obesity phenotype observed in C. elegans after RNAi knockdown of their orthologs puf-8, fbf-2, rpac-19, gon-1, let-355, glp-1, pop-1, and mys-1. On the other hand, higher NT5C2 expression positively correlates with obesity ( Fig 3B ), which is in line with the lean phenotype observed in C. elegans after RNAi-driven knockdown of the ortholog gene Y71H10B.1. A parsimonious hypothesis derived from these correlations would be that if RNAi against a C. elegans gene leads to obesity, and a low-expression variant of its ortholog gene is associated with increased BMI in humans, then the ortholog of the C. elegans hit gene is likely to have a causal role in human obesity. Although we appreciate the caveats of the premises leading to this hypothesis, including that changes in expression may be compensatory and not causal mechanisms, we present these analyses as an approximation to the likelihood that the human and C. elegans genes have causal roles in obesity in both organisms. Therefore, as for the most part, the expression associations with BMI in humans go in the same direction as they do in mice and C. elegans, we hypothesize that the orthologs of the C. elegans hit genes are likely to have conserved causal roles in human obesity.

( A ) Bi-weight Mid-correlations (median based correlation metric) of mouse gene expression and metabolic traits in adipose tissue of the HMDP cohort. Genes negatively associated with fat mass are shown on the left, and positive associations on the right. Bolded mouse ortholog names indicate that the expression of the mouse and the worm genes are associated with fat storage (fat mass in mice) in the same direction. ( B ) Association (Beta of association) between human gene expression in the subcutaneous adipose tissue and clinical traits in the METSIM cohort. Genes negatively associated with BMI are shown on the left. Positive associations are shown on the right. Bolded human ortholog gene names indicate that the expression of the human and the worm gene are associated with fat storage (BMI in humans) in the same direction. Underlined human ortholog names indicate the same correlation sign is observed in worms, mice, and humans. ( C ) Number of published metabolic and non-metabolic trait GWAS associations for each human ortholog present in the GWAS catalog. The assumption to interpret these data is that genes with variants mostly associated to metabolic traits would more likely be directly involved in metabolic or metabolic-related functions, whereas genes with GWAS variants in mostly non-metabolic traits are more likely to have pleiotropic effects including indirect weight loss or gain. Colors distinguish association with metabolic (black) and non-metabolic (grey) traits.

In the HMDP cohort, we found 12 mouse orthologs of the C. elegans hits (Adamts9, Dhx33, and Kat8 were not measured in this study). Remarkably, 7 out of the 8 genes whose expression negatively correlates with obesity traits in the mouse, also lead to obesity when they are knocked down via RNAi in C. elegans ( Fig 3A –bolded names in the gene set to the left), suggesting that the mouse variants would lead to loss or reduced function of these genes and that these seven genes would play similar roles in the regulation of fat storage in C. elegans and the mouse. Specifically, lower expression of Pum2, Polr1d, Notch4, Tcf7l2, Tcf12, Psmc3, and Zfhx3 correlates with increased body fat percentage, fat mass, body weight, and total mass in the mouse, which is comparable to knockdown of the orthologs puf-8, fbf-2, rpac-19, glp-1, pop-1, hlh-2, rpt-5, and zfh-2 causing obesity in C. elegans. On the other hand, we found Nt5c2 expression to positively correlate with obesity traits in the mouse, which is in line with the knockdown of the C. elegans ortholog–Y71H10B.1– leading to leanness in C. elegans ( Fig 3A –bolded name in the gene set to the right).

The 16 confirmed worm hits correspond to 16 unique human genes ( S1 Table ). The phenotypes in C. elegans suggest these 16 genes may have a conserved causal role in obesity. In the absence of monogenic human diseases or knock-out mice lines, we decided to approximate a test of this hypothesis using three publicly available datasets: (1) Gene expression data from adipose tissue from the Hybrid Mouse Diversity Panel [ 71 ] (HMDP)–a cohort of well-phenotyped male and female mice fed a high-fat diet; (2) Subcutaneous adipose tissue gene expression data from the METSIM cohort–a thoroughly phenotyped cohort of Finnish men [ 56 ]; and (3) the GWAS catalog ( www.ebi.ac.uk/gwas/home ). With the HMDP and METSIM datasets, we could define whether reduced or increased expression of the human obesity candidate genes (or their mouse orthologs) were associated with obesity. The GWAS catalog enabled us to investigate to what extent the gene may be specifically affecting metabolic disease, as opposed to promoting more general sickness with an indirect impact on body-mass index (BMI) or waist-hip ratio (WHR).

Throughout this figure: Scale bars = 200μm. Error bars = S.E.M. N = number of independent biological replicates. Statistical significance was assessed via ratio t-test, *p≤ 0.05, **p≤0.01, ***p≤0.001 and ****p≤0.0001. ( A ) Representative images of the body fat content and distribution in worms treated with RNAi against Y71H10B.1/NT5C2 (from the L1 stage) and let-767/HSD17B12 (from the L4 stage because let-767 RNAi from the L1 stage results in severe developmental arrest; S1C Fig ). ( B-C ) ORO signal intensity in RNAi-treated worms for the treatments shown in panel A. Each data point represents the measurement of a single worm relative to the EV mean. N = 3. ( D ) Representative image of the body fat content and distribution in worms treated with RNAi against rpt-5/PSMC3 (from the L1 stage). ( E ) ORO signal intensity in rpt-5 RNAi-treated worms. Each data point represents the measurement of a single worm relative to the EV mean. N = 3.

We identified 23 genes altering fat storage in the primary screen carried out in 96-well plates. To validate the causal role of these genes in C. elegans reared in standard conditions, we retested the RNAi-driven phenotypes in worms grown in 6cm RNAi plates. In the retest, as in the primary screen, animals were treated with RNAi from the L1 stage. In this validation setup, ORO signal per worm was quantitated using ImageJ. We confirmed 13 out of 14 of the primary obese-gene hits: puf-8 (human gene PUM2), fbf-2 (PUM2), glp-1 (NOTCH4, EYS), let-355 (DHX33), mys-1 (KAT8), rpac-19 (POLR1D), gon-1 (ADAMTS9), hlh-2 (TCF12), pop-1 (TCF7L2), zfh-2 (ZFHX3), eif-6 (EIF6), nst-1 (GLN3), and Y46E12BL.2 (RRP12) ( Fig 1B , 1C , 1D and 1E and S1 Table ). Of these obese genes, knockdown of all but puf-8 also caused sterility; hence, hereinafter we refer to these hits as sterile genes ( Fig 1C ). However, the seemingly exceptional phenotype of puf-8 may be due to our binary sterile versus fertile classification. In fact, puf-8 deficiency has been linked to germline phenotypes including reduced germline, reduced progeny size, and a tumorous germline [ 65 , 66 ]. If confirmed with a null mutant, the quantitative (as opposed to qualitative) fertility phenotype of puf-8 opens the exciting possibility of using it to more finely dissect the mechanisms determining soma versus germline nutrient allocation. Furthermore, RNAi against gon-1, hlh-2, pop-2, and zfh-2 promoted an unusual sterility phenotype, in which animals showed extensive fat depletion around the vulva ( Fig 1C ), suggesting a possible change in fat tissue distribution when germline/eggs are lacking that also warrants future study. Distinctively, eif-6, nst-1, and Y46E12BL.2 showed a developmental-delay phenotype ( Fig 1D ). A link between obesity and infertility, and obesity and compromised growth, has been extensively documented [ 40 , 67 – 69 ]. It would then be important for future studies to define whether obesity is the cause or consequence of these phenotypes.

RNAi treatments, fat staining with ORO, and imaging for the screen were performed in duplicate and retested in three independent biological replicates as described in the Materials and Methods section. Using Cellprofiler feature extraction coupled to Cellprofiler Analyst classification of the microphotographs of fat-stained worms, RNAi treatments were categorized as follows: (1) wild type: >50% of the worms in the well showed quantities and distribution of ORO signal indistinguishable from that of animals treated with empty vector RNAi control (EV); (2) obese: after RNAi treatment >50% of the worms in these populations showed more intensity or broader distribution of the ORO signal than the parallel EV controls, suggesting that the gene is necessary to prevent obesity in animals fed a standard diet; and (3) lean: >50% of the worms in the RNAi-treated population showed lesser intensity or narrower distribution of the ORO signal than the parallel EV controls, suggesting that the gene is necessary to store normal levels of fat in C. elegans fed a standard diet. The gene knockdowns that exhibited a consistent lean or obese phenotype in three independent replicates were selected for further validation ( Fig 1A and S1 Table ).

Although we identified 386 C. elegans orthologs of 207 genes associated with obesity traits in humans, only 293 of these 386 ortholog genes were available in the Ahringer (original and supplementary) [ 60 ] or the Vidal [ 61 ] C. elegans genome-wide RNAi libraries ( Fig 1A and S1 Table ). Therefore, we built an RNAi sub-library consisting of these 293 worm genes for screening, which corresponded to 187 human-obesity gene candidates (workflow in S1A Fig ). To increase the efficiency of the RNAi knockdown we used the RNAi-hypersensitive mutant rrf-3(pk1426) as the genetic background for the screen [ 62 ], after confirming it has wild type quantity and distribution of fat as made evident by the fat-specific dye Oil Red O (ORO) ( S1B Fig ). Although the loss of rrf-3 function makes C. elegans hypersensitive to RNAi (including in neurons, [ 62 ]), it is important to keep in mind that some gene targets may not be accessible to RNAi even in this genetic background. Further, gene-gene and gene-environment interactions may be altered by mutation of rrf-3. As such, the phenotypic outcomes of our screen are conditioned by the choice of genetic background (rrf-3), which may alter the phenotype of genes with background-specific phenotypic effects (e.g., only evident in metabolically sensitized backgrounds [ 63 , 64 ] or in the wild type background).

Throughout this figure: Error bars = S.E.M. N = numbers of independent biological replicates. *p≤ 0.05, **p≤0.01, ***p≤0.001 and ****p≤0.0001. ( A ) Summary of the meta-analysis and C. elegans RNAi screen results. GWAS obesity candidate genes from three studies [ 56 – 58 ] were selected for RNAi screen. ( B-D ) Representative images of empty vector RNAi controls (EV) and RNAi-treated worms stained with oil red O (ORO). All images are in the same magnification, scale bar = 200μm. Hit genes were categorized into 3 groups: ( B ) Obese without obvious pleiotropies; ( C ) Obese with sterility. Blue boxes denote unusual “fat depletion around the vulva” phenotype; and ( D ) obese with developmental delay. ( E ) Quantification of ORO signal intensity in RNAi-treated worms for all treatments shown in panels B-D. Each data point represents the measurement of a single worm relative to the EV mean. N = 3. Ratio t-test was used to make comparisons between EV and the treatments.

To identify genes that potentially contribute to human obesity, we exploited published meta-analyses of genome-wide association studies (GWAS) of obesity traits [ 51 , 52 ]. Together, three studies report over 1,200 loci associated with an increased body-mass index (BMI), waist/hip ratio (a measure of fat distribution), or other metabolic traits. However, as is standard for these kinds of studies [ 53 – 55 ], the majority of the variants were not linked to genes. Therefore, we searched through the three previous studies for high-quality candidate genes linked to obesity loci. First, work by our group used eQTL analysis of 770 subcutaneous adipose samples from the Metabolic Syndrome in Men (METSIM) study [ 56 ] to link about 680 of these loci to 211 obesity gene candidates ( S1 Table ). We previously found genetic variants that were associated with both the expression of the candidate gene in subcutaneous adipose tissue and with various metabolic GWAS traits. For the present study, we considered a subset of 211 genes that are associated with obesity-related traits only. We performed Mendelian Randomization analyses to confirm that these genes are likely causal for obesity. Secondly, 120 novel gene candidates were taken based on the genomic location from a study that searched for novel loci associated with BMI in a trans-ancestral meta-analysis of 173,430 samples [ 57 ] Finally, Chu et al. [ 58 ] analyzed 2.6 million SNPs in up to 9,594 women and 8,738 men of European, African, Hispanic, and Asian ancestry, and based on the genomic location, they predicted 11 novel genes as associated with ectopic fat accumulation in the cohort [ 58 ], which we added to our candidate list. Together, we extracted 340 novel genes associated with obesity traits in humans from the three studies ( S1 Table , [ 56 – 58 ]). Next, using the comparative genomic analysis tool Ortholist2 [ 59 ], we defined that 207 out of the 340 human candidate genes (67%) had orthologs in C. elegans ( Fig 1A and S1 Table ). However, in some cases, a human gene had more than one C. elegans ortholog; therefore, we identified a total of 386 C. elegans orthologs that corresponded to the 207 human gene candidates ( Fig 1A and S1 Table ). We then moved to use in vivo functional genomics screening to determine which of the human-obesity candidate genes have causal relationships with fat storage in C. elegans.

Discussion

GWAS is a powerful approach to identify loci associated with obesity because large cohorts are sampled across the arc of socioeconomic statuses, physical activity, eating habits, microbiota composition, and genetic diversity. However, connecting the resulting loci to the specific genes that promote or prevent obesity remains challenging. Obstacles include the large candidate-locus lists, defining the specific gene/s influenced by the genetic variants, and the time-consuming nature of molecular, cellular, and physiological studies [98]. For instance, a single decision such as where (e.g., tissue) and when (e.g., developmental stage) to inactivate or hyperactivate a candidate gene may change the outcome of the phenotypic assessment. As a result, comparatively few GWAS loci have been causally linked to the disease of interest. In the case of obesity, there are ~950 loci associated with BMI [51] and ~350 loci associated with waist-hip ratio adjusted BMI [52], yet very few genes have been validated and fewer druggable targets exist. Therefore, methods that can test the causality of GWAS loci quickly and effectively were needed.

In this study, we introduced two complementary approaches to validate potential obesity GWAS genes in a high-throughput manner: bioinformatic analyses of publicly available datasets and high throughput in vivo RNAi screening in the model organism C. elegans. This nematode has been used as a genetically-tractable animal model for uncovering and characterizing the cellular and molecular functions of genes related to complex human diseases such as obesity. Despite significant differences with mammals including lack of specialized adipose tissue for fat storage [99], absence of key mammalian fat regulators such as leptin [100], and a distinct cholesterol metabolism comparing to mammals [101], the core metabolic pathways (e.g., Beta-oxidation) and signals regulating fat build-up and mobilization, fasting, healthspan and lifespan (e.g., Insulin) are present and carry out comparable functions in both C. elegans and mammals [102]. Furthermore, key regulators of metabolism and lifespan were first discovered in C. elegans and then supported by mammalian studies (e.g., DAF-16/FOXO [103]). Nevertheless, there are caveats associated with using RNAi in a nematode model system to test human obesity variants. The caveats range from false negatives due to the distinct biology and anatomy of C. elegans and mammals–as described above–to the fact that some human variants would be gains of function whereas RNAi causes loss of function. Additionally, gene-environment interactions are very complex and they play critical roles on the effect of gene variants. As such, the chosen genetic background may limit the discovery of genes with phenotypic effects only penetrant in specific mutant or wild-type genetic backgrounds. Nevertheless, as demonstrated in this study, combining gene candidate generation from human GWAS with testing causality via in vivo RNAi in C. elegans can aid in identifying genes contributing to complex human diseases such as obesity.

We here reveal 11 novel obese genes (fbf-2, gon-1, hlh-2, let-355, mys-1, nst-1, pop-1, puf-8, rpac-19, rpt-5 and Y46E12BL.2) and two novel lean/DIO suppressor genes (let-767, and pho-1). We also retrieved three obese genes (eif-6, glp-1 and zfh-2) and one lean/DIO suppressor gene (Y71H10B.1) that were previously linked to fat metabolism or obesity.

Among the known fat genes, we previously showed that inactivation of the C. elegans Notch receptor, glp-1, causes obesity [67]. By contrast, although the human orthologs of glp-1, NOTCH4 and EYS, were associated with obesity in GWAS [56,57], they have not been causally linked to the disease. The combination of experimental validation of glp-1 as an obesity gene in C. elegans with our database analyses showing that expression of NOTCH4 and EYS negatively correlates with BMI and other markers of metabolic disease in mice and humans, puts the spotlight on NOTCH4 and EYS as potential anti-obesity targets. However, not all hits from our screen showed a tight phenotypic correlation between worms and mammals. Unlike the obesity phenotype observed upon whole-body knockdown of eif-6 in C. elegans fed a regular diet, Eif6 heterozygous mice had reduced body weight gain compared to their wild-type littermates [104]. Similarly, knockdown of zfh-2 in C. elegans leads to obesity in animals fed a regular diet whereas heterozygous mutation of the mouse ortholog, Zfhx3/Atbf1, leads to reduced body weight gain [105]. Nevertheless, it is difficult to evaluate the body-weight phenotypes of Eif6 and Zfhx3 heterozygous mutant mice because these mutations lead to pleiotropic effects including perinatal mortality, growth retardation, and severe behavioral deficits [104,105], and neither body fat mass nor even circulating triglycerides were reported in the single in vivo mouse mutant studies available to date for each of these genes. Further emphasizing the need for future analyses of these genes, reduced expression of Zfhx3 is strongly associated with increased body fat, fat mass, and markers of metabolic syndrome including insulin sensitivity and high cholesterol in mice (Fig 3A), suggestive of a role in obesity for this gene. Therefore, the apparent contradictory effects of inactivating eif-6 and zfh-2 in C. elegans and constitutive inactivation of the murine orthologs need further investigation.

In addition to the three previously characterized genes, we identified 14 C. elegans genes not yet causally linked to obesity. The biological functions of most of these genes and their mammalian orthologs have not been fully elucidated. Nonetheless, some have been characterized to a level that enables us to propose hypotheses about their roles in fat storage. For instance, KAT8 –the human ortholog of C. elegans mys-1 –promotes acetylation of fatty acid synthase (FASN), which leads to reduced FASN activity [106]. FASN is the terminal enzyme in de novo lipogenesis; therefore, it is reasonable to hypothesize that reduced KAT8 activity might increase lipogenesis and hence promote obesity, a phenotype that would be in line with the obesity phenotype we describe here for knockdown of the C. elegans ortholog mys-1 and the negative correlation between KAT-8 expression and obesity in humans. Another example, TCF7L2 –the human ortholog of C. elegans pop-1– has been shown as a key regulator of glucose homeostasis. It has been reported that overexpression of a nuclear isoform of Tcf7l2 (mice ortholog) in high-fat diet fed mice improves glucose tolerance, while depletion of Tcf7l2 in mice causes higher glucose levels and impaired glucose tolerance [107,108]. Although the mechanism is not fully elucidated, impaired glucose homeostasis has been strongly associated with obesity in numerous studies [109]. The protective role of Tcf7l2 in glucose homeostasis may suggest a protective role in obesity too. In support of this notion, expression of Tcf7l2 in mice and TCF7L2 in humans negatively correlates with BMI, which is in line with our observation that knockdown of pop-1 promotes obesity in C. elegans. Therefore, future study of the role of TCF7L2 in human obesity is warranted.

Increased sugar intake, especially fructose from high-fructose corn syrup, was suggested to be a leading cause of the current prevalence of obesity [12–14]. Fructose has been reported to have even more detrimental effects than glucose in healthspan [15]. Here we demonstrated that a HFrD not only disrupts lipid homeostasis but causes premature health deterioration a death in C. elegans; a result that is in line with two studies showing that dietary supplementation of 5 and 10% fructose reduces lifespan in C. elegans [48,49]. Interestingly, one of these studies also showed that feeding 1 or 2% fructose extended C. elegans lifespan [49]. This is intriguing because 1% is the dose of fructose we use in the present study, and we observed a dramatic reduction in the lifespan of C. elegans subjected to this dietary regimen. However, there are experimental details that may explain the discrepancies. Zheng et al supplemented fructose to worm media plates seeded with E. coli OP50, while we used plates seeded with E. coli HT115. We made the choice of performing our whole study on animals fed the RNAi-competent strain E. coli HT115 to maintain the dietary composition consistent between the primary screen and the follow-up studies. The relevance of E. coli to C. elegans metabolic phenotypes is well documented. Fat storage, healthspan, and lifespan depend on the bacteria composition [84,110,111]. Further, recent large-scale E. coli mutant screens revealed microbial biochemical pathways influencing C. elegans fat accumulation [112] and longevity [113]. Based on these studies, we hypothesize that the discrepancies in the C. elegans lifespan phenotypes even when fed the same dose of fructose may be due to the use of different E. coli strains in the two studies. This is a very interesting observation since little is known about the molecular underpinnings defining the outcomes of different diet-microbiome-host three-way interactions in the development of obesity. Therefore, our C. elegans HFrD model can serve as an informative platform to molecularly dissect such complex interactions in future studies.

Importantly, in this study, we define that knockdown of Y71H10B.1, let-767, and pho-1 prevents the development of DIO in C. elegans. The mammalian ortholog of C. elegans Y71H10B.1, named Nt5c2, encodes for a purine nucleotidase. Nt5c2 knockout mice gain less weight when fed a high-fat diet [114], in line with the DIO suppressor phenotype observed in C. elegans treated with RNAi against Y71H10B.1. Furthermore, using adipose tissue gene expression from the METSIM cohort, we defined that the expression of the human ortholog, NT5C2, positively correlates with waist-to-hip ratio and circulating triglycerides, suggesting that inactivation of Y71H10B.1/NT5C2. would have an antiobesity effect in animal species ranging from C. elegans to humans. Similarly, mice carrying a mutation in Acp2, the murine ortholog of the C. elegans DIO suppressor gene pho-1, are smaller and gain less weight than the wild-type controls [115]. Further, again using the METSIM cohort, we found that the expression of the human ortholog, ACP2, positively correlates with body weight and total triglycerides. Interestingly, the function of pho-1-like genes in fat metabolism may be conserved even across kingdoms, as reduction of ACP4 –the predominant ortholog of pho-1 in Arabidopsis–leads to a decrease in total leaf lipids [116]. The congruency of phenotypic effects between inactivation of Y71H10B.1 and pho-1 in C. elegans and their orthologs in mammals supports the notion that these genes would be causally linked to obesity across animals. In addition the similarities strengthen our confidence in the value of our nematode screening approach to defining which GWAS loci are causally linked to obesity.

Given the causal link between obesity and age-related diseases [117], we sought to define whether knocking down of the three DIO suppressor genes–pho-1, let-767, and Y71H10B.1– ameliorates the negative impact of a high-fructose diet on C. elegans health and lifespan. We found all 3 DIO suppressors of obesity also partially suppressed the detrimental effects of HFrD on health and lifespan. To approximate whether the orthologs of pho-1, let-767, and Y71H10B.1 may also impact healthspan in humans, we mined the GWAS catalog. One variant (rs75393320-C) that mapped to the human ortholog of pho-1, ACP2, is associated with HDL-C [118]. HDL-C has been suggested to have a protective role in cardiovascular health [119], which is a leading cause of premature death in humans.

With respect to let-767, its mammalian ortholog Hsd17b12 is a member of the hydroxysteroid dehydrogenase superfamily specifically involved in the synthesis of arachidonic acid [120]. Knock out of Hsd17b12 in mice causes embryonic death at the E8.5 stage [121], which is in line with the C. elegans developmental delay phenotype we report here. As for humans, we show that the expression of HSD17B12 is positively associated with LDL-C and negatively associated with HDL-C, implying a detrimental effect of HSD17B12 on health. Further, other 18 variants mapped to HSD17B12 are associated with diseases including Type-2 diabetes, cardiovascular disease, and coronary artery diseases in the GWAS Catalog, suggesting a role for HSD17B12 in the modulation of healthspan that is in line with our observation that depletion of let-767 improves healthspan in C. elegans.

Regarding the human ortholog of Y71H10B.1, NT5C2, there are 77 variants mapped to NT5C2 associated with a variety of disease-related traits (besides obesity traits), including hypertension, abnormal blood pressure, coronary artery disease, and cardiovascular diseases in the GWAS Catalog. Moreover, knockout of Nt5c2 (in mice) not only protects against high-fat diet-induced weight gain and adiposity but also improves insulin sensitivity and reduces hyperglycemia [114], all in line with our observation of improved healthspan and lifespan in C. elegans treated with RNAi against Y71H10B.1.

In summary, we identified 17 genes that promote or prevent C. elegans obesity, and the early onset of organismal deterioration and death associated with obesity. By combining the results of in vivo studies in C. elegans with analyses of mouse and human GWAS databases, we defined that the sign of the correlation between the expression levels of the mouse and human genes and their associated clinical traits matches, for the most part, the phenotypic effects of knocking down these genes in C. elegans, suggesting conserved causality and pharmacological potential for these obesity genes.

[END]

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