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Follow This Diet To Reverse Insulin Resistance \u0026 Diabetes in 2 Weeks! We train the health care Boost cognitive focus of healhh, today, offering professionals Healtu knowledge, Insulin sensitivity and gut health and abilities to deliver exemplary care. UC Davis sensitivith and education programs offer Ribose biosynthesis pathway highest quality training, skills and Healing sensitiviyt lead change and improve health for all. We believe improving health for all is possible. So, our collaborative research includes clinical, translational and basic science studies. News, blogs and publications from UC Davis Health with the latest health care, patient, faculty, leadership, medical, science and research news and innovations. A study led by UC Davis has found significant differences in gut bacteria between Black and white women, even after accounting for their insulin sensitivity status.Insulin sensitivity and gut health -
Insulin resistance, independent of body mass index, tends to be greater in Black compared to White women, yet the mechanisms to explain these differences are not completely understood. The gut microbiome is implicated in the pathophysiology of obesity, insulin resistance and cardiometabolic disease.
Only two studies have examined race differences in Black and White women, however none characterizing the gut microbiome based on insulin sensitivity by race and sex.
Our objective was to determine if gut microbiome profiles differ between Black and White women and if so, determine if these race differences persisted when accounting for insulin sensitivity status.
We conducted analyses by self-identified race and by race plus insulin sensitivity status e. insulin sensitive versus insulin resistant as determined by HOMA-IR.
Alpha diversity did not differ by race nor by race and insulin sensitivity status. Our findings suggest that the gut microbiome, particularly lower beta diversity and greater Actinobacteria , one of the most abundant species, may play an important role in driving cardiometabolic health disparities of Black women, indicating an influence of social and environmental factors on the gut microbiome.
Citation: Price CA, Jospin G, Brownell K, Eisen JA, Laraia B, Epel ES Differences in gut microbiome by insulin sensitivity status in Black and White women of the National Growth and Health Study NGHS : A pilot study.
PLoS ONE 17 1 : e Editor: Brenda A. Wilson, University of Illinois Urbana-Champaign, UNITED STATES. Received: April 26, ; Accepted: October 28, ; Published: January 19, Copyright: © Price et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Competing interests: The authors have declared that no competing interests exist. Type 2 diabetes T2D prevalence in Blacks is almost twice that of Whites [ 1 ]. It is expected that almost half of Black women in the U.
will develop diabetes [ 2 ]. Obesity promotes increased inflammation and insulin resistance. Greater insulin resistance is reported in Black women compared to White women in some [ 5 , 6 ], but not all studies [ 7 — 9 ], even when matched for BMI.
However, the mechanisms contributing to the progression of insulin resistance in Black women are not well-understood [ 7 , 10 , 11 ]. Ancestral genetic differences have been linked to insulin resistance in Black individuals [ 12 , 13 ], but the recognition of race as a social construct highlights social determinants of health as important mediators [ 14 ].
Understanding the etiology of insulin resistance development in Black women requires an interdisciplinary approach that integrates the social determinants of health e.
environmental factors with physiological outcomes. One such approach is the understanding the role of the gut microbiome in the pathway of cardiometabolic disease development. The gut microbiome is influenced largely by environmental and social factors, such as diet and psychological stress [ 15 — 17 ], and is linked to the development of insulin resistance and T2D [ 18 — 20 ].
The three most predominant gut bacteria species at the phylum level are Firmicutes , Bacteroidetes , and Actinobacteria [ 21 — 24 ]. Greater Firmicutes and Actinobacteria but lower Bacteroidetes characterize microbial communities in obesity and T2D [ 25 — 27 ]; although this finding is not consistent amongst studies [ 28 ].
At the genus level Ruminococcus , Blautia of the Firmicutes phylum and Fusobactria of the Fusiobacteria phylum and are positively associated with T2D, whereas Bifidobacteria and Bacteroides of the Actinobacteria and Bacteroidetes phylum, respectively appear to be protective against T2D [ 19 ].
Lower gut bacteria diversity, both within sample alpha diversity and diversity within populations beta diversity , is also associated with lower metabolic health and insulin resistance [ 29 — 31 ]. Bacteria diversity differs amongst ethnic groups [ 32 ].
Despite advances in microbiome research, few studies have examined the role of gut bacteria in T2D health disparities affecting specific populations [ 33 ].
Three studies in men and women of African-decent examined the microbiome in the context of obesity [ 34 ], high blood pressure [ 35 ] and colorectal cancer [ 36 ]. Although study design and outcomes were variable amongst these studies, together they suggest associations between Bacteroidetes with race and glucose tolerance, regardless of body weight.
One study observed a greater ratio of Firmicutes to Bacteroidetes in Blacks versus other race and ethnicities [ 36 ]. However unlike the previous studies in healthy participants, this study was conducted in a small sample of colorectal cancer patients.
There are no studies examining the role of the microbiome with insulin resistance in Black women. The majority of microbiome studies in Black women have focused on the vaginal microbiome in relation to fertility and reproductive health [ 37 — 39 ].
To our knowledge, only three studies have examined gut bacteria from fecal samples of Black women [ 40 — 42 ]. Of these, only one compared bacteria profiles between overweight, pre- and post-menopausal, Black and White women. This study found a greater relative abundance of Bacteroides , a genus within the Bacteroidetes phylum [ 41 ].
Comparisons between Black women in the U. versus lean Ghanaian women found Bacteroides and family Lachnospiraceae to be higher in U. Black women [ 40 ]. This was also accompanied by differences in beta diversity between groups and lower alpha diversity in U. Black women. Carson and colleagues observed racial differences in bacteria beta diversity between race groups but no differences for within sample alpha diversity [ 41 ].
Similar findings were observed in postmenopausal Black and White women [ 42 ]. Only one study has linked beta diversity, Bacteroidetes or Lachnospiraceae to obesity and insulin resistance in Black women, however this study compared ethnic differences U.
No studies in the U. have investigated these relationhips by sex and race differences to help explain racial disparities in health. The gut microbiome may provide us greater insight into furthering our understanding of obesity and type 2 diabetes risk in Black women. Given the paucity of literature on this topic, we collected fecal samples from Black and White women of the National Growth and Health Study NGHS to explore whether or not gut bacteria profiles differed by race and insulin sensitivity status.
We hypothesized that we would identify gut bacteria profiles, specifically lower Firmicutes to Bacteroidetes ratio and lower alpha diversity that would be associated with greater insulin resistance in Black women. The original NGHS examined risk factors for cardiovascular disease in socioeconomically-diverse Black and White girls from childhood ages 9—10 through young adulthood.
Participants were recruited from three regions of the U. who self-identified their race as Black or White. Participant eligibility and study protocol is described elsewhere.
Briefly, participants were eligible to enroll in the study if, at the time of enrollment, they were: 1. Not currently pregnant, 2. Had not given birth, experienced a miscarriage, or had an abortion in the past three months, 3.
were not currently living abroad and 4. were not institutionalized or in prison. Participants who provided written consent for protocol number were enrolled. Informed consent was obtained during the in-person visit for local participants.
For participants who had relocated farther than 65 miles from Berkeley, CA, consent forms were mailed and signed consent forms were returned to study staff by mail. This study was approved by the Institutional Review Board at the University of California, Berkeley.
Body weight was measured during the follow-up annual in-person visit at either their home or local clinic. The visit protocol is described elsewhere, but briefly included completion of consents, anthropometric measures and blood draw appointment scheduling. Blood draws were collected for the measurement of fasting glucose and insulin concentrations.
A total of women provided fecal samples for the current analysis. All study participants were given the choice to complete a stool sample using a Ubiome collection kit UBiome, San Francisco, CA.
Participants were eligible to complete a stool sample after they enrolled in the study, completed their consent forms with study staff, and completed the baseline survey. Samples were collected between March and September During the visit, remote or in-person, each participant was provided a Ubiome sample kit that was labeled with their unique kit ID and specific instructions for use.
Study staff also reviewed the instructions in detail with the participants and answered any questions. Participants were instructed on sample collection hygiene and sterility including avoiding contamination of collection swab to anything other than the fecal sample e.
fingers, hair, floor, etc. Participants were also asked by study staff if they had taken antibiotics recently. If antibiotics were taken, the participant was instructed to wait three months from the date that they ended their antibiotic course to permit gut microbiome recovery before collecting the sample.
Research suggests that gut microbiome mostly recovers between 1 to 1. Participants were also asked to disclose if they had any gastrointestinal conditions, as inflammatory bowel syndrome, inflammatory bowel disease [ 47 ] as well as other conditions that can influence the gut microbiome.
After completing the sample, participants used a pre-packaged envelope to send their sample directly to Ubiome for processing. Processing of UBiome fecal samples have been previously described [ 48 ]. Briefly, samples were lysed by bead-beading and DNA was extracted in a class room using guanidine thiocyanate silica column-based purification method.
Universal primers containing Illumina tags and barcodes were used for polymerase chain reaction PCR amplification of 16S rRNA genes. PCR products were pooled, column purified, and size-selected through microfluidic DNA fractionation [ 49 ].
Sequencing was performed in a pair-end modality on the Illumina NexSeq platform rendering 2 x bp pair-end sequences. After quality control of the raw sequence files, to ensure each sample had paired end reads information, samples were processed using the dada2 1.
Taxonomy was inferred using the DECIPHER package and the silva database. Taxonomic ranks were as follows: kingdom, phylum, class, order, family, genus and species.
Data from this study are available at datadyrad [ 51 ]. Descriptives: A univariate analysis determined unequal distribution for BMI, fasting glucose, fasting insulin and HOMA-IR. To test for differences between groups in these outcomes, we used nonparametric statistical analysis with Wilcoxon test.
Difference in age was determined by general linear model. Differences in distribution of insulin sensitivity status between race groups were determined by chi-square test. Microbiota analyses: Our analyses focused on identifying potential differences in gut health based on phylum and family relative abundance, and diversity measures alpha and beta.
The data manipulation and statistical analysis of bacteria taxonomy, such as alpha and beta diversity, was done using phyloseq 1. Alpha diversity, a measure of diversity within each sample, was measured by three measures: Shannon Index, Simpson, or Chao.
The dataset was rarefied to 10, reads and non-normally distributed variables were log-transformed. Some samples were discarded through rarefaction set at 10, reads for the alpha diversity measures. Shannon and Simpson Indices both weigh relative microbial community richness based on amplicon sequence variant ASV and evenness of representation within a sample [ 53 , 54 ].
The Chao Index determines richness calculating the expected diversity of ASV based on the presence of all species present within a sample [ 55 ].
To measure beta diversity, a measure of diversity between groups, we used the principal coordinate analysis PCoA from Bray-Curtis dissimilarity distances available through the phyloseq R package.
Microbiota analyses by race and insulin resistance: To determine differences in alpha diversity and taxonomy by race, we used a general linear model with tukey post-test for comparisons between groups by race Black vs White.
Based on prior studies demonstrating the significant effect of BMI on bacteria profiles, all models included BMI as a covariate. Post-hoc analyses tested for differences between groups categorized by race and insulin sensitivity classification Black insulin sensitive IS Black ; Black insulin resistant IR Black ; White insulin sensitivity IS White ; White insulin resistant IR White.
All reported p-values include adjustments for BMI. Differences in relative abundance at the phylum level were adjusted for Bonferroni corrections based on 7 observations at the phylum level and 30 observations at the family level. Participant characteristics are listed in Table 1.
Both groups had a greater proportion of insulin sesntive versus insulin resistant women. However, after filtering for prevalence of bacteria, only 57 taxa remained: 7 phyla, 30 families and 20 genera.
Here, we report only diversity measures, phylum and family relative abundances. Data at the genus level was undetected in several samples resulting in low yield and insufficient sample size for comparison. Seven phyla were detected in our participants: Actinobacteria, Firmicutes, Bacteroidetes, Fusobacteria, Epsilonbacteraeota, Verrucomicrobria, and Proteobacteria.
Including HOMA-IR in the model and testing for an interaction with race did not improve these outcomes. Black women in our sample had approximately twice the proportion of Actinobacteria 6. Relative abundance was measured by 16S rRNA gene PCR and sequencing. The relative abundance of the phyla Verrucomicrobia and Proteobacteria represented a mean of 3.
BMI significantly contributed to the variability between groups for Proteobacteria BMI, p There was a 4 fold higher level of Verrucomicrobia in Black women with insulin resistance vs White women with insulin resistance 4. We did not observe any statistically significant differences in the relative abundance of Fusobacteria or Epsiolobacteria between groups.
Phylum distribution by race and insulin sensitivity status is depicted in Fig 2. We detected 30 different taxa at the family level Fig 3 and only 20 taxa at the genus level.
We found that due to low yield of bacteria at the genus level, differences were statistically significant at the family level but not at the genus level. Therefore, only family was included in the final analysis. We did not observe any significant differences by race for any of the bacteria we identified at the family level.
There were no differences by race amongst insulin resistant women. Relative abundance of A Lachnospiraceae and B Clostridales Family XIII in fecal samples by race and insulin sensitivity status.
Beta diversity by race at the phylum and family levels are depicted in the principal coordinate analysis PCoA plots in Fig 5A and 5B. Fig 6 depicts PCoA plots when participants were categorized based on both race and insulin sensitivity status IS or IR. Principal coordinate analysis PCoA of relative abundance of bacteria in fecal samples by A phylum and B family in White and Black women.
To our knowledge, this is the first investigation to report differences in gut bacteria by insulin sensitivity status in Black versus White women, and only the third study examining gut microbiota between Black and White women in the US.
Our study is also the largest conducted to date and the first to focus on premenopausal Black and White women. Since few studies have characterized microbial communities in women with and without insulin resistance, we sought to explore the gut microbiome as one potential mechanism explaining disproportionately higher insulin resistance in Black women.
Our analyses found that the gut microbiome differed both by race alone and when stratified by insulin sensitivity status, at the phylum and family levels. Specifically, we found significant differences in beta diversity and Actinobacteria by race, that were further explained by insulin sensitivity status.
Consistent with epidemiological findings [ 56 ], Black women in our cohort presented higher BMI as compared with White women. Therefore, in order to determine race differences independent of obesity, all analyses included adjustments for BMI.
An important finding in our study is the significantly greater relative abundance of phylum Actinobacteria in Black women. Our finding supports previous research demonstrating greater Actinobacteria in obese compared to lean individuals [ 57 ]. However, this is in contrast to a study by Yang and colleagues that found Actinobacteria to be lower in relative abundance in the oral microbiome of Blacks compared to Whites [ 58 ].
These opposing results may simply reflect differences in the type of biospecimen collected e. oral vs fecal [ 59 ]. Further analyses in our study found that when comparing race differences based on insulin sensitivity status, the presence of greater Actinobacteria in Black women as compared with White women was only observed amongst insulin resistant individuals; there were no racial differences amongst insulin sensitive women.
First, they examined metabolites in the feces of over adults at their regular health checkups. They compared this metabolome with the insulin resistance levels obtained from the same people.
People with higher insulin resistance contained more bacteria from the taxonomic order Lachnospiraceae than from other orders. Additionally, microbiomes that included Lachnospiraceae were associated with excess fecal carbohydrates.
Thus, a gut microbiota dominated by Lachnospiraceae was related to both insulin resistance and feces with excessive monosaccharides. At the same time, insulin resistance and monosaccharide levels were lower in participants whose guts contained more Bacteroidales-type bacteria than other types.
They then set out to see the direct effect of bacteria on metabolism in culture and then in mice. In culture, Bacteroidales bacteria consumed the same kinds of monosaccharides that were found in the feces of people with high insulin resistance, with the species Alistipes indistinctus consuming the greatest variety.
In obese mice, the team looked at how treatment with different bacteria affected blood sugar levels. They found that A. indistinctus lowered blood sugar and reduced insulin resistance and the amount of carbohydrates available to the mice. These results were compatible with the findings from human patients and have implications for diagnosis and treatment.
Likewise, treatment with probiotics containing A. indistinctus might improve glucose intolerance in those with pre-diabetes. Additionally, they discovered that gut microbiomes with higher levels of Flavonifractor tended to have lower insulin sensitivity.
Mark Goodarzi , Ph. Low insulin sensitivity also called insulin resistance refers to low responses of these tissues to insulin. Most people with insulin resistance compensate by producing more insulin.
When insulin production is insufficient to deal with insulin resistance, blood sugars rise and type 2 diabetes occurs. In the last several years, multiple studies, including this o ne from , have found that individuals with type 2 diabetes have lower levels of a certain type of bacteria that produces a type of short-chain fatty acid called butyrate.
Goodarzi said. The researchers found that while most bacteria that produce butyrate were associated with better insulin sensitivity, a few were associated with insulin resistance.
Goodarzi explained. For the study, investigators analyzed data from people who had not previously been diagnosed with diabetes. Of the participants, were non-Hispanic whites, and were African-American. None of the participants had recently experienced severe gastrointestinal illness or used medicines like antibiotics that could impact the microbiome.
Researchers found 28 of the participants had diabetes, and an additional were classified as having prediabetes. Participants with diabetes and prediabetes were combined into a single group and were compared with the participants with healthy glucose tolerance.
Participants were asked to collect a stool sample 1—2 days before coming to the clinic. Researchers found that participants with abnormalities in blood glucose levels were older, more often male, and had higher BMI. They discovered that Coprococcus and related bacteria had beneficial effects on insulin sensitivity.
But Flavonifractor , despite producing butyrate, was associated with insulin resistance. The analyses found 10 bacteria associated with a lower rate of blood sugar levels fluctuating abnormally and two bacteria associated with adverse associations on blood sugar levels.
Goodarzi told MNT. If so proven, clinical trials will be the next step to determine whether modulating these bacteria via prebiotics, probiotics, or antibiotics, depending on the bacterial targets are a viable option to prevent or treat diabetes.
One type of Healing hewlth in the gut may Insylin to seensitivity development of Type 2 diabetes, while another may protect from the Healing, Energy production and healthy fats Healing early results from an ongoing, prospective study Insulin sensitivity and gut health Antidepressant for premenstrual dysphoric disorder investigators at Cedars-Sinai. The study, published in the peer-reviewed journal Diabetesfound people wnd higher levels xensitivity Healing bacterium called Coprococcus tended to have higher insulin sensitivity, while those whose microbiomes had higher levels of the bacterium Flavonifractor tended to have lower insulin sensitivity. For years, investigators have sought to understand why people develop diabetes by studying the composition of the microbiome, which is a collection of microorganisms that include fungi, bacteria and viruses that live in the digestive tract. The microbiome is thought to be affected by medications and diet. Mark Goodarzi, MD, PhDthe director of the Endocrine Genetics Laboratory at Cedars-Sinai, is leading an ongoing study that is following and observing people at risk for diabetes to learn whether those with lower levels of these bacteria develop the disease.
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