A million-person genetic analysis points to FNIP1 as a key regulator of human energy metabolism, linking rare loss-of-function variants to healthier fat distribution, lower liver fat, and substantially lower odds of cardiometabolic disease.
Study: FNIP1 variants are associated with favourable metabolism in 1 million humans. Image Credit: Explode / Shutterstock
In a recent study published in the journal Nature, researchers conducted an unprecedentedly vast exome sequencing study to investigate the genetic basis of human energy metabolism. The study leveraged data from 1,032,116 individuals across America, Europe, and Asia to evaluate rare protein-coding variants in relation to their carriers' triglyceride-to-high-density-lipoprotein cholesterol (TG:HDL) ratio.
Study findings identified 59 independent genes enriched among liver and adipose master regulators that were independently associated with participants’ TG:HDL ratios, thereby implicating them in human energy balance, storage, and metabolism.
Furthermore, the study demonstrated that ultra-rare loss-of-function variants in the FNIP1 gene were associated with favorable fat distribution, lower liver fat, improved glycemic control, and around 60% lower odds of a composite cardiometabolic disease outcome, highlighting this gene as a target for future research.
Background
Extensive metabolic and cardiovascular research has established altered energy and lipid metabolism as shared contributors to global cardiometabolic morbidity. These altered physiological states are now known to significantly increase patients’ risk of coronary artery disease (CAD), type 2 diabetes (T2D), and metabolic-dysfunction-associated steatotic liver disease (MASLD).
In parallel, clinical epidemiology has shown that an individual’s triglyceride-to-high-density-lipoprotein cholesterol (TG:HDL) ratio has been proposed as a biomarker of metabolic state and is associated with insulin resistance, T2D, and CAD. In the present study, the researchers further examined its relationships with visceral adiposity, ectopic fat, and systemic inflammation.
Unfortunately, despite these separate lines of evidence, scientists hitherto lacked exome sequencing datasets at sufficient scale and ancestral diversity to systematically investigate rare coding variants associated with energy and lipid metabolism and identify potential therapeutic targets for cardiometabolic interventions.
About the study
The present study aimed to address this persistent knowledge gap and inform future cardiometabolic research by combining exome sequencing, common-variant imputation, and health outcome profiling data. The study’s sample cohort comprised 1,032,116 participants from 11 international cohorts across America, Europe, and Asia, representing the largest exome sequencing dataset in the field to date.
The study’s primary line of investigation was an exome-wide gene-burden test for rare coding variants (minor allele frequency < 1%) associated with the TG:HDL ratio. Herein, statistical analyses were adjusted to account for 1,617 independent common variant signals.
The researchers then focused on folliculin-interacting protein 1 (FNIP1), a previously established inhibitor of mitochondrial biogenesis and energy expenditure, which has been observed to act downstream of AMP-activated protein kinase (AMPK).
They used small interfering RNA (siRNA)-mediated knockdown of FNIP1 in primary human hepatocytes, thereby allowing the researchers to assess changes in the expression of genes involved in lipid catabolism and lysosomal function.
Additionally, the study used adeno-associated virus (AAV8-gRNA) gene editing of Fnip1, Fnip2, and their interactor (Flcn) in Cas9-expressing mice challenged with a high-fat, high-fructose diet to functionally investigate the implicated pathway in vivo.
Study findings
The study’s epidemiological components confirmed that an elevated TG:HDL ratio was associated with significantly greater visceral fat volume and hepatic steatosis, while a higher baseline ratio predicted an increased risk of incident T2D, myocardial infarction, MASLD, and liver cirrhosis across African, admixed American, East Asian, South Asian, and European ancestry groups.
The exome-wide discovery pipeline identified 60 genes reaching exome-wide significance, 59 of which remained independently associated after conditional analysis (P < 1.04 x 10-7). Of these 59 genes, 44 represented novel rare-coding-variant associations, while 23 (39%) encoded approved or clinical-stage drug targets.
Most importantly, the study isolated ultra-rare predicted loss-of-function (pLOF) variants in the FNIP1 gene (allele frequency ~0.01%). Participants carrying these variants had a 0.5 standard deviation (s.d.) lower TG:HDL ratio (P = 1.1 x 10-10), favorable body-fat distribution, lower liver fat, reduced alanine aminotransferase (ALT) levels, and lower glycated hemoglobin, alongside around 60% lower odds of the composite cardiometabolic disease outcome (odds ratio [OR] = 0.39, P = 0.0011) than non-carriers.
Mechanistically, the study found that siRNA-mediated FNIP1 knockdown in primary human hepatocytes induced expression of lysosomal and lipid-catabolism genes. In vivo murine experiments provided further functional support, demonstrating that combined hepatic knockdown of Fnip1 and Fnip2, or knockdown of Flcn alone, protected mice from diet-induced weight gain, reduced liver triglycerides, and enhanced insulin sensitivity, whereas Fnip1 or Fnip2 inhibition alone did not protect against weight gain in mice.
Conclusions
The present study implicates the FNIP1-FLCN pathway as an important regulator of human energy expenditure and metabolic health. The authors concluded that hepatocyte-targeted inhibition of FNIP1, such as via GalNAc-conjugated siRNA, may represent a tractable therapeutic strategy for the future treatment of cardiometabolic diseases, particularly because selective liver targeting may help avoid adverse effects associated with systemic loss of function in this pathway.
However, the authors noted important uncertainties, including species-specific functional redundancy between mouse and human paralogs (Fnip1 versus Fnip2) and the necessity for further experimental evaluation of the efficacy and safety of pathway modulation in humans. Liver safety also remains an important consideration, given previous mouse evidence linking broader FLCN loss to liver injury and carcinogenesis, although the present study observed favorable hepatic phenotypes following liver-targeted pathway inhibition.
These limitations notwithstanding, this study demonstrates how mega-scale exome sequencing can uncover biologically important pathways in human metabolism and identify potential therapeutic targets for common cardiometabolic diseases.
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