Body fat distribution is a major, heritable risk factor for cardiometabolic disease, independent of overall adiposity. Using exome-sequencing in 618,375 individuals (including 160,058 non-Europeans) from the UK, Sweden and Mexico, we identify 16 genes associated with fat distribution at exome-wide significance. We show 6-fold larger effect for fat-distribution associated rare coding variants compared with fine-mapped common alleles, enrichment for genes expressed in adipose tissue and causal genes for partial lipodystrophies, and evidence of sex-dimorphism. We describe an association with favorable fat distribution (p = 1.8 × 10-09), favorable metabolic profile and protection from type 2 diabetes (~28% lower odds; p = 0.004) for heterozygous protein-truncating mutations in INHBE, which encodes a circulating growth factor of the activin family, highly and specifically expressed in hepatocytes. Our results suggest that inhibin βE is a liver-expressed negative regulator of adipose storage whose blockade may be beneficial in fat distribution-associated metabolic disease.

New treatments are being evaluated for lipodystrophy; however, limited information is available on the patient experience. Results of a prior patient panel showed that hunger and temperature-related symptoms were an issue for participants. Therefore, evaluation of any changes in these symptoms is recommended for inclusion in new treatment options. The objective of this study was to further understand the patient experience and to evaluate newly developed items of hunger and temperature regulation.

Sirtuins are NAD(+)-dependent protein deacetylases. They mediate adaptive responses to a variety of stresses, including calorie restriction and metabolic stress. Sirtuin 3 (SIRT3) is localized in the mitochondrial matrix, where it regulates the acetylation levels of metabolic enzymes, including acetyl coenzyme A synthetase 2 (refs 1, 2). Mice lacking both Sirt3 alleles appear phenotypically normal under basal conditions, but show marked hyperacetylation of several mitochondrial proteins. Here we report that SIRT3 expression is upregulated during fasting in liver and brown adipose tissues. During fasting, livers from mice lacking SIRT3 had higher levels of fatty-acid oxidation intermediate products and triglycerides, associated with decreased levels of fatty-acid oxidation, compared to livers from wild-type mice. Mass spectrometry of mitochondrial proteins shows that long-chain acyl coenzyme A dehydrogenase (LCAD) is hyperacetylated at lysine 42 in the absence of SIRT3. LCAD is deacetylated in wild-type mice under fasted conditions and by SIRT3 in vitro and in vivo; and hyperacetylation of LCAD reduces its enzymatic activity. Mice lacking SIRT3 exhibit hallmarks of fatty-acid oxidation disorders during fasting, including reduced ATP levels and intolerance to cold exposure. These findings identify acetylation as a novel regulatory mechanism for mitochondrial fatty-acid oxidation and demonstrate that SIRT3 modulates mitochondrial intermediary metabolism and fatty-acid use during fasting.

Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10-3) and candidate genes from knockout mice (P = 5.2 × 10-3). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.

Sequencing of large cohorts offers an unprecedented opportunity to identify rare genetic variants and to find novel contributors to human disease. We used gene-based collapsing tests to identify genes associated with glucose, HbA1c and type 2 diabetes (T2D) diagnosis in 379,066 exome-sequenced participants in the UK Biobank. We identified associations for variants in GCK, HNF1A and PDX1, which are known to be involved in Mendelian forms of diabetes. Notably, we uncovered novel associations for GIGYF1, a gene not previously implicated by human genetics in diabetes. GIGYF1 predicted loss of function (pLOF) variants associated with increased levels of glucose (0.77 mmol/L increase, p = 4.42 × 10-12) and HbA1c (4.33 mmol/mol, p = 1.28 × 10-14) as well as T2D diagnosis (OR = 4.15, p = 6.14 × 10-11). Multiple rare variants contributed to these associations, including singleton variants. GIGYF1 pLOF also associated with decreased cholesterol levels as well as an increased risk of hypothyroidism. The association of GIGYF1 pLOF with T2D diagnosis replicated in an independent cohort from the Geisinger Health System. In addition, a common variant association for glucose and T2D was identified at the GIGYF1 locus. Our results highlight the role of GIGYF1 in regulating insulin signaling and protecting from diabetes.

To investigate the role of adipose tissue in reproductive function and mammary gland development and function, we have examined lipodystrophic (LD) mice. LD mice of both sexes are sterile, but fertility can be restored with leptin injections. Mammary glands from lipodystrophic mice were rudimentary and lacked terminal end buds. Leptin-injected LD mice were able to become pregnant, showed normal pregnancy-associated glandular proliferation despite a smaller glandular area, were able to produce a small amount of milk that had grossly normal content of milk proteins and neutral lipids, but could not sustain pups to weaning. In order to separate the individual requirements for 1) adipokines such as leptin, 2) estradiol, and 3) physical epithelial-adipocyte interactions, we performed a series of experiments with both lipodystrophic mice and ob (obese mice with a mutation in the lep gene encoding the adipokine leptin) mice that received either estradiol treatment or preadipocyte transplant. The resulting fat pad did not rescue the defect in mammary gland development in lipodystrophic mice. The defect also could not be rescued with estradiol pellets. Ob/ob mice, like LD mice, lack leptin and estradiol, but retain adipose tissue. Ob mice have defective mammary gland development. However, in striking contrast to what was observed in lipodystrophic mice, reconstitution of a WT fat pad in ob mice rescued the defect in mammary gland development. Estradiol treatment did not rescue mammary gland development in ob mice. Therefore direct interaction between mammary gland epithelia and adipocytes is a requirement for full invasion and expansion of the gland, but is not required for glandular proliferation during pregnancy and milk production.

Phenome-wide association studies (PheWASs) have been a useful tool for testing associations between genetic variations and multiple complex traits or diagnoses. Linking PheWAS-based associations between phenotypes and a variant or a genomic region into a network provides a new way to investigate cross-phenotype associations, and it might broaden the understanding of genetic architecture that exists between diagnoses, genes, and pleiotropy. We created a network of associations from one of the largest PheWASs on electronic health record (EHR)-derived phenotypes across 38,682 unrelated samples from the Geisinger's biobank; the samples were genotyped through the DiscovEHR project. We computed associations between 632,574 common variants and 541 diagnosis codes. Using these associations, we constructed a "disease-disease" network (DDN) wherein pairs of diseases were connected on the basis of shared associations with a given genetic variant. The DDN provides a landscape of intra-connections within the same disease classes, as well as inter-connections across disease classes. We identified clusters of diseases with known biological connections, such as autoimmune disorders (type 1 diabetes, rheumatoid arthritis, and multiple sclerosis) and cardiovascular disorders. Previously unreported relationships between multiple diseases were identified on the basis of genetic associations as well. The network approach applied in this study can be used to uncover interactions between diseases as a result of their shared, potentially pleiotropic SNPs. Additionally, this approach might advance clinical research and even clinical practice by accelerating our understanding of disease mechanisms on the basis of similar underlying genetic associations.