Y

Yan Y. Lam

Rutgers, The State University of New Jersey

ORCID: 0000-0002-5724-1142

Publishes on Gut microbiota and health, Diet and metabolism studies, Adipokines, Inflammation, and Metabolic Diseases. 54 papers and 5.6k citations.

54Publications
5.6kTotal Citations

Is this you? Claim your profile.

Add your photo, update your bio, and get notified when your ranking changes.

Top publicationsby citations

Gut bacteria selectively promoted by dietary fibers alleviate type 2 diabetes
Liping Zhao, Feng Zhang, Xiaoying Ding et al.|Science|2018
Cited by 2.3k

The gut microbiota benefits humans via short-chain fatty acid (SCFA) production from carbohydrate fermentation, and deficiency in SCFA production is associated with type 2 diabetes mellitus (T2DM). We conducted a randomized clinical study of specifically designed isoenergetic diets, together with fecal shotgun metagenomics, to show that a select group of SCFA-producing strains was promoted by dietary fibers and that most other potential producers were either diminished or unchanged in patients with T2DM. When the fiber-promoted SCFA producers were present in greater diversity and abundance, participants had better improvement in hemoglobin A1c levels, partly via increased glucagon-like peptide-1 production. Promotion of these positive responders diminished producers of metabolically detrimental compounds such as indole and hydrogen sulfide. Targeted restoration of these SCFA producers may present a novel ecological approach for managing T2DM.

Increased Gut Permeability and Microbiota Change Associate with Mesenteric Fat Inflammation and Metabolic Dysfunction in Diet-Induced Obese Mice
Yan Y. Lam, Connie Ha, Craig Campbell et al.|PLoS ONE|2012
Cited by 605Open Access

We investigated the relationship between gut health, visceral fat dysfunction and metabolic disorders in diet-induced obesity. C57BL/6J mice were fed control or high saturated fat diet (HFD). Circulating glucose, insulin and inflammatory markers were measured. Proximal colon barrier function was assessed by measuring transepithelial resistance and mRNA expression of tight-junction proteins. Gut microbiota profile was determined by 16S rDNA pyrosequencing. Tumor necrosis factor (TNF)-α and interleukin (IL)-6 mRNA levels were measured in proximal colon, adipose tissue and liver using RT-qPCR. Adipose macrophage infiltration (F4/80⁺) was assessed using immunohistochemical staining. HFD mice had a higher insulin/glucose ratio (P = 0.020) and serum levels of serum amyloid A3 (131%; P = 0.008) but reduced circulating adiponectin (64%; P = 0.011). In proximal colon of HFD mice compared to mice fed the control diet, transepithelial resistance and mRNA expression of zona occludens 1 were reduced by 38% (P<0.001) and 40% (P = 0.025) respectively and TNF-α mRNA level was 6.6-fold higher (P = 0.037). HFD reduced Lactobacillus (75%; P<0.001) but increased Oscillibacter (279%; P = 0.004) in fecal microbiota. Correlations were found between abundances of Lactobacillus (r = 0.52; P = 0.013) and Oscillibacter (r = -0.55; P = 0.007) with transepithelial resistance of the proximal colon. HFD increased macrophage infiltration (58%; P = 0.020), TNF-α (2.5-fold, P<0.001) and IL-6 mRNA levels (2.5-fold; P = 0.008) in mesenteric fat. Increased macrophage infiltration in epididymal fat was also observed with HFD feeding (71%; P = 0.006) but neither TNF-α nor IL-6 was altered. Perirenal and subcutaneous adipose tissue showed no signs of inflammation in HFD mice. The current results implicate gut dysfunction, and attendant inflammation of contiguous adipose, as salient features of the metabolic dysregulation of diet-induced obesity.

Effects of dietary fat profile on gut permeability and microbiota and their relationships with metabolic changes in mice
Yan Y. Lam, Connie Ha, Jenny Hoffmann et al.|Obesity|2015
Cited by 216Open Access

OBJECTIVE: To distinguish the effects of dietary fat profile on gut parameters and their relationships with metabolic changes and to determine the capacity of n-3 fatty acids to modify gut variables in the context of diet-induced metabolic dysfunctions. METHODS: Mice received control or high-fat diets emphasizing saturated (HFD-sat), n-6 (HFD-n6), or n-3 (HFD-n3) fatty acids for 8 weeks. In another cohort, mice that were maintained on HFD-sat received n-3-rich fish oil or resolvin D1 supplementation. RESULTS: HFD-sat and HFD-n6 induced similar weight gain, but only HFD-sat increased index of insulin resistance (HOMA-IR), colonic permeability, and mesenteric fat inflammation. Hydrogen sulfide-producing bacteria were one of the major groups driving the diet-specific changes in gut microbiome, with the overall microbial profile being associated with changes in body weight, HOMA-IR, and gut permeability. In mice maintained on HFD-sat, fish oil and resolvin D1 restored barrier function and reduced inflammation in the colon but were unable to normalize HOMA-IR. CONCLUSIONS: Different dietary fat profiles led to distinct intestinal and metabolic outcomes that are independent of obesity. Interventions targeting inflammation successfully restored gut health but did not reverse systemic aspects of diet-induced metabolic dysfunction, implicating separation between gut dysfunctions and disease-initiating and/or -maintaining processes.

Guild-based analysis for understanding gut microbiome in human health and diseases
Guojun Wu, Naisi Zhao, Chenhong Zhang et al.|Genome Medicine|2021
Cited by 213Open Access

To demonstrate the causative role of gut microbiome in human health and diseases, we first need to identify, via next-generation sequencing, potentially important functional members associated with specific health outcomes and disease phenotypes. However, due to the strain-level genetic complexity of the gut microbiota, microbiome datasets are highly dimensional and highly sparse in nature, making it challenging to identify putative causative agents of a particular disease phenotype. Members of an ecosystem seldomly live independently from each other. Instead, they develop local interactions and form inter-member organizations to influence the ecosystem's higher-level patterns and functions. In the ecological study of macro-organisms, members are defined as belonging to the same "guild" if they exploit the same class of resources in a similar way or work together as a coherent functional group. Translating the concept of "guild" to the study of gut microbiota, we redefine guild as a group of bacteria that show consistent co-abundant behavior and likely to work together to contribute to the same ecological function. In this opinion article, we discuss how to use guilds as the aggregation unit to reduce dimensionality and sparsity in microbiome-wide association studies for identifying candidate gut bacteria that may causatively contribute to human health and diseases.