Physiological Characterization

Physiological Characterization

We have entered a new era in which technological developments coupled with expanded computational power and increased statistical sophistication have enabled the global query of discrete biological axes. Manufacturing advances introduced arrays that could measure mRNA transcript levels or DNA single nucleotide variation comprehensively in a single experiment. A deeper knowledge of the patterns of human genetic variation allowed for the explosion of genome-wide association studies (GWAS). Remarkable efficiency gains in high-throughput next-generation sequencing seeded whole-exome and whole-genome sequencing studies, as well as ancillary explorations of the transcriptome (RNAseq), transcription factor binding sites (ChiPseq), open chromatin (ATAC-seq), the epigenome, or the microbiome. Mass spectroscopy can be applied to the study of small metabolites or proteins in organic fluids, including post-translational modifications. In this manner, multiple dimensions of the molecular architecture of biological systems can be interrogated with respect to native and perturbed metabolic states. This technological progress has been accompanied by concomitant enhancements in bioinformatic and analytical tools, often shared publicly in the pre-competitive space.

Crucially, nowadays all of these advances can increasingly be deployed in the organism of interest, the human. Health care systems have digitalized clinical information, and increasingly made the electronic medical record available to clinical investigation. Large private and even national biobanks have been created to streamline this research function, and both funding bodies and scientific journals have required data sharing in central repositories as a condition for research support or publication. We therefore live in the midst of a revolution of big data across all domains of the human experience, ranging from the molecular to the societal dimensions. We practice medicine and conduct research within an unprecedented whirlwind of data, spanning from populations to the individual. It will soon be possible to capture the metabolic state of a single patient at the molecular and cellular levels with great precision through multiple time points in his/her development.

An outstanding but crucial challenge to the field is our ability to integrate these disparate data sources in a manner that informs a holistic view of an organism, such that synergy begets understanding. While genomic explorations have only explained a minor fraction of the genetic contribution to the phenotype, in conjunction with physiological measures they can be used to improve our nosology of the disease, and begin to characterize the clusters that may define specific subtypes.

The integration of physiologic and pharmacogenetic information with genetic discoveries can offer additional insight. By perturbing a live human with a drug that targets a given gene and assessing the response to the perturbation, one may be able to “close the loop” and demonstrate that a gene associated with disease is indeed involved in producing the phenotype of interest. Conversely, drugs that modulate a specific limb of the glucose homeostatic system (insulin secretion, central or peripheral insulin sensitivity), if shown to have differential responses depending on genotype, may serve to prioritize genes in a given associated region.

The Florez lab works with longitudinal observational cohorts (e.g. Framingham Heart Study, the CHARGE Consortium, SEARCH, CAMP), richly phenotyped clinical trials (e.g. the Diabetes Prevention Program, Look AHEAD, TODAY), healthcare biobanks (Partners Biobank, UK Biobank), or our own pharmacogenetic or nutrigenetic studies (SUGAR-MGH, SIGMA) to study genotype-phenotype correlations and analyze physiological measurements to link genetic variation to human organismal biology.

DPP

The Diabetes Prevention Program randomized participants at high risk of T2D (based on impaired glucose tolerance, an elevated fasting glucose and overweight) to placebo, metformin, or intensive lifestyle modification. Both the metformin and lifestyle interventions proved effective in preventing or delaying the onset of diabetes [DPP NEJM paper], and these effects were sustained [DPP Lancet …

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PHARMGen

The Patients with Hyperglycemia Assessed for Response to Medications by Genetics study is a retrospective clinical cohort of several thousand participants with T2D culled from electronic medical record databases where prescription information and glycemic response is available. Volunteers provide a DNA sample and pharmacogenetic assessments of drug response in a real world setting can be …

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SIGMA MMTT

The SIGMA mixed-meal tolerance test study challenges non-diabetic participants with a high-calorie, high-carbohydrate meal reflective of current US dietary patterns, before and after a short course of metformin. Their glycemic, hormonal and metabolomic responses to the dietary and pharmacological perturbations can be studied according to genotype at selected loci. …

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SUGAR-MGH

The Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans is a pharmacogenetic resource in which 1,000 volunteers who were na├»ve to T2D medications received a glipizide challenge and a short course of metformin, after which they underwent an oral glucose tolerance test (OGTT). Their glycemic, hormonal and metabolomic …

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Type 2 diabetes variants disrupt function of SLC16A11 through two distinct mechanisms

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ?20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that …

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Impact of type 2 diabetes susceptibility variants on quantitative glycemic traits reveals mechanistic heterogeneity

Patients with established type 2 diabetes display both ?-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic …

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The influence of rare genetic variation in SLC30A8 on diabetes incidence and beta-cell function

CONTEXT/OBJECTIVE: The variant rs13266634 in SLC30A8, encoding a ?-cell-specific zinc transporter, is associated with type 2 diabetes. We aimed to identify other variants in SLC30A8 that increase diabetes risk and impair ?-cell function, and test whether zinc intake modifies this risk. DESIGN/OUTCOME: We sequenced exons in SLC30A8 in 380 Diabetes Prevention Program (DPP) participants and …

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Detailed physiologic characterization reveals diverse mechanisms for novel genetic loci regulating glucose and insulin metabolism in humans

OBJECTIVE: Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin processing, secretion, and sensitivity to help elucidate their role in regulation of glucose control, insulin secretion and/or action. RESEARCH DESIGN AND METHODS: We investigated associations of loci identified by …

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