Dataset Information

Transmission of human-associated microbiota along family and social networks.

ABSTRACT: The human microbiome, described as an accessory organ because of the crucial functions it provides, is composed of species that are uniquely found in humans1,2. Yet, surprisingly little is known about the impact of routine interpersonal contacts in shaping microbiome composition. In a relatively 'closed' cohort of 287 people from the Fiji Islands, where common barriers to bacterial transmission are absent, we examine putative bacterial transmission in individuals' gut and oral microbiomes using strain-level data from both core single-nucleotide polymorphisms and flexible genomic regions. We find a weak signal of transmission, defined by the inferred sharing of genotypes, across many organisms that, in aggregate, reveals strong transmission patterns, most notably within households and between spouses. We were unable to determine the directionality of transmission nor whether it was direct. We further find that women harbour strains more closely related to those harboured by their familial and social contacts than men, and that transmission patterns of oral-associated and gut-associated microbiota need not be the same. Using strain-level data alone, we are able to confidently predict a subset of spouses, highlighting the role of shared susceptibilities, behaviours or social interactions that distinguish specific links in the social network.

SUBMITTER: Brito IL

PROVIDER: S-EPMC7450247 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

Transmission of human-associated microbiota along family and social networks.

Brito Ilana L IL Gurry Thomas T Zhao Shijie S Huang Katherine K Young Sarah K SK Shea Terrence P TP Naisilisili Waisea W Jenkins Aaron P AP Jupiter Stacy D SD Gevers Dirk D Alm Eric J EJ

Nature microbiology 20190325 6

The human microbiome, described as an accessory organ because of the crucial functions it provides, is composed of species that are uniquely found in humans1,2. Yet, surprisingly little is known about the impact of routine interpersonal contacts in shaping microbiome composition. In a relatively 'closed' cohort of 287 people from the Fiji Islands, where common barriers to bacterial transmission are absent, we examine putative bacterial transmission in individuals' gut and oral microbi ...[more]

PMID: 30911128

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Project description:Note: Data Use Restrictions: <ul> <li>The data must only be used for genetic research projects solely in the area of health-related social-network research.</li> </ul> This study compiles detailed information on family and social ties linked to participants in the offspring cohort of the Framingham Heart Study. The investigators took computerized information from self-report data used by the FHS for over 30 years to facilitate health exam scheduling. These tracking sheets asked participants to identify people close to them, which were assumed by the investigators to indicate a social tie. Individuals are listed as "egos" (if the ties are from their perspective) and/or "alters" (if they are linked as a friend or family members to one of the other participants). All egos were FHS offspring participants while alters could be FHS participants in any cohort or non-participants. This information was combined with internal FHS pedigree data on family ties to list family member alters (as well as the nature of their relationship). The resultant dataset therefore includes each ego-alter tie, the nature of their relationship and the start and end dates for their ties for each of seven waves for the offspring study. Due to privacy concerns, all exam dates for individuals are listed relative to the initial FHS exam date. The study investigators chose a random, confidential date, to which all initial exam dates are linked (by number of months from random date to initial exam date). With this information, researchers can have access to the temporal relationships among participants' exam dates while remaining unaware of the actual exam dates for individual participants. During each clinic exam cycle, the participants undergo a detailed examination including physical examination, medical history, laboratory testing, and electrocardiogram. Over the years, other tests (that may not be performed at every exam cycle) have included pulmonary function, lifestyle, physical function, cognitive function questionnaires, and various noninvasive cardiovascular tests including echocardiograms. This study involves phenotypic data from these exams including (when available) basic body measurements (height, weight, blood pressure), laboratory values (blood sugar levels, LDL levels), information on smoking and alcohol use, and tests of depression and cognitive functioning. Important links to apply for individual-level data <ol> <li><a href="http://dbgap.ncbi.nlm.nih.gov/aa/wga.cgi?view_pdf&stacc=phs000153.v3.p3" target="_blank">Data Use Certification Requirements (DUC)</a></li> <li><a href="GetPdf.cgi?id=phd001183.1" target="_blank">Instructions to Request Authorized Access</a></li> <li><a href="http://view.ncbi.nlm.nih.gov/dbgap-controlled" target="_blank">Apply here for controlled access to individual level data</a></li> <li><a href="GetPdf.cgi?id=phd000317" target="_blank">Participant Protection Policy FAQ</a></li> </ol> In 1948, researchers recruited men and women from the town of Framingham, Massachusetts, beginning the first round of extensive physical examinations and lifestyle interviews that would later be analyzed for common patterns related to CVD development. Initially, the Framingham Heart Study enrolled 5,209 men and women from the Framingham area who were between the ages of 28 and 62 years. Beginning in 1971, the Framingham Heart Study enrolled 5,124 men and women, who were either offspring of the original cohort or spouses of those offspring. In 2002, 4,095 third generation participants (men and women) were enrolled.

Project description:BackgroundSexually transmitted infections spread across contact networks. Partner elicitation and notification are commonly used public health tools to identify, notify, and offer testing to persons linked in these contact networks. For HIV-1, a rapidly evolving pathogen with low per-contact transmission rates, viral genetic sequences are an additional source of data that can be used to infer or refine transmission networks.Methods and findingsThe New York City Department of Health and Mental Hygiene interviews individuals newly diagnosed with HIV and elicits names of sexual and injection drug using partners. By law, the Department of Health also receives HIV sequences when these individuals enter healthcare and their physicians order resistance testing. Our study used both HIV sequence and partner naming data from 1342 HIV-infected persons in New York City between 2006 and 2012 to infer and compare sexual/drug-use named partner and genetic transmission networks. Using these networks, we determined a range of genetic distance thresholds suitable for identifying potential transmission partners. In 48% of cases, named partners were infected with genetically closely related viruses, compatible with but not necessarily representing or implying, direct transmission. Partner pairs linked through the genetic similarity of their HIV sequences were also linked by naming in 53% of cases. Persons who reported high-risk heterosexual contact were more likely to name at least one partner with a genetically similar virus than those reporting their risk as injection drug use or men who have sex with men.ConclusionsWe analyzed an unprecedentedly large and detailed partner tracing and HIV sequence dataset and determined an empirically justified range of genetic distance thresholds for identifying potential transmission partners. We conclude that genetic linkage provides more reliable evidence for identifying potential transmission partners than partner naming, highlighting the importance and complementarity of both epidemiological and molecular genetic surveillance for characterizing regional HIV-1 epidemics.

Dataset Information

Transmission of human-associated microbiota along family and social networks.

Publications

Transmission of human-associated microbiota along family and social networks.

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