White adipose tissue and circadian rhythm dysfunctions in obesity : Pathogenesis and available therapies

A combined neuroendocrine, metabolic, and chronobiological view can help to better understand the multiple and complex mechanisms involved in obesity development and maintenance, as well as to provide new effective approaches for its control and treatment. Indeed, we have currently updated data on the whole adipogenic process involved in white adipose tissue (WAT) mass expansion, namely due to a mechanism whereby WAT cells become hypertrophic, thus inducing a serious local (WAT) inflammatory condition that in turn, will impair not only the cross-talk between the hypothalamus and the WAT, but also favoring the development of deep and widespread neuroendocrine-metabolic dysfunction. Moreover, we also have revisited the circadian clock genes involved in dysfunctional WAT mass expansion and the mechanisms that may lead to obesity development, including early metabolic dysfunctions, enhanced oxidative stress and distorted energy homeostasis. The epigenetic changes of clock genes driving metabolic disease and obesity development have also been included in this review. Finally, we have also underlined the relevance of metabolic homeostasis regulation by central and peripheral organ clocks, sleep disturbances, nutrients, and feeding time, as key factors in obesity development as well as both, classical and chronotherapeutic approaches for its prevention and treatment.Centro de Endocrinología Experimental y Aplicad

Population sequencing of two endocannabinoid metabolic genes identifies rare and common regulatory variants associated with extreme obesity and metabolite level

Abstract Background Targeted re-sequencing of candidate genes in individuals at the extremes of a quantitative phenotype distribution is a method of choice to gain information on the contribution of rare variants to disease susceptibility. The endocannabinoid system mediates signaling in the brain and peripheral tissues involved in the regulation of energy balance, is highly active in obese patients, and represents a strong candidate pathway to examine for genetic association with body mass index (BMI). Results We sequenced two intervals (covering 188 kb) encoding the endocannabinoid metabolic enzymes fatty-acid amide hydrolase (FAAH) and monoglyceride lipase (MGLL) in 147 normal controls and 142 extremely obese cases. After applying quality filters, we called 1,393 high quality single nucleotide variants, 55% of which are rare, and 143 indels. Using single marker tests and collapsed marker tests, we identified four intervals associated with BMI: the FAAH promoter, the MGLL promoter, MGLL intron 2, and MGLL intron 3. Two of these intervals are composed of rare variants and the majority of the associated variants are located in promoter sequences or in predicted transcriptional enhancers, suggesting a regulatory role. The set of rare variants in the FAAH promoter associated with BMI is also associated with increased level of FAAH substrate anandamide, further implicating a functional role in obesity. Conclusions Our study, which is one of the first reports of a sequence-based association study using next-generation sequencing of candidate genes, provides insights into study design and analysis approaches and demonstrates the importance of examining regulatory elements rather than exclusively focusing on exon sequences

A mechanism-based operational definition and classification of hypercholesterolemia

In contrast to strong evidence-based clinical recommendations for lipid-lowering treatment, there is no analogous definitive diagnostic definition of hypercholesterolemia and its various subtypes. For many clinicians, guideline indications for hypolipidemic treatment can become broadly conflated with hypercholesterolemia in a non-specific sense. In this statement, we propose a unified definition and mechanism-based classification of hypercholesterolemia, which in turn should help to stratify patients and guide efficient diagnosis without interfering with the current strategies of ASCVD risk reduction

Channel estimation techniques for next generation mobile communication systems

Mención Internacional en el título de doctorWe are witnessing a revolution in wireless technology, where the society is demanding new services, such as smart cities, autonomous vehicles, augmented reality, etc. These challenging services not only are demanding an enormous increase of data rates in the range of 1000 times higher, but also they are real-time applications with an important delay constraint. Furthermore, an unprecedented number of different machine-type devices will be also connected to the network, known as Internet of Things (IoT), where they will be transmitting real-time measurements from different sensors. In this context, the Third Generation Partnership Project (3GPP) has already developed the new Fifth Generation (5G) of mobile communication systems, which should be capable of satisfying all the requirements. Hence, 5G will provide three key aspects, such as: enhanced mobile broad-band (eMBB) services, massive machine type communications (mMTC) and ultra reliable low latency communications (URLLC). In order to accomplish all the mentioned requirements, it is important to develop new key radio technologies capable of exploiting the wireless environment with a higher efficiency. Orthogonal frequency division multiplexing (OFDM) is the most widely used waveform by the industry, however, it also exhibits high side lobes reducing considerably the spectral efficiency. Therefore, filter-bank multi-carrier combined with offset quadrature amplitude modulation (FBMC-OQAM) is a waveform candidate to replace OFDM due to the fact that it provides extremely low out-ofband emissions (OBE). The traditional spectrum frequencies range is close to saturation, thus, there is a need to exploit higher bands, such as millimeter waves (mm-Wave), making possible the deployment of ultra broad-band services. However, the high path loss in these bands increases the blockage probability of the radio-link, forcing us to use massive multiple-input multiple-output (MIMO) systems in order to increase either the diversity or capacity of the overall link. All these emergent radio technologies can make 5G a reality. However, all their benefits can be only exploited under the knowledge and availability of the channel state information (CSI) in order to compensate the effects produced by the channel. The channel estimation process is a well known procedure in the area of signal processing for communications, where it is a challenging task due to the fact that we have to obtain a good estimator, maintaining at the same time the efficiency and reduced complexity of the system and obtaining the results as fast as possible. In FBMC-OQAM, there are several proposed channel estimation techniques, however, all of them required a high number of operations in order to deal with the self-interference produced by the prototype filter, hence, increasing the complexity. The existing channel estimation and equalization techniques for massive MIMO are in general too complex due to the large number of antennas, where we must estimate the channel response of each antenna of the array and perform some prohibitive matrix inversions to obtain the equalizers. Besides, for the particular case of mm-Wave, the existing techniques either do not adapt well to the dynamic ranges of signal-to-noise ratio (SNR) scenarios or they assume some approximations which reduce the quality of the estimator. In this thesis, we focus on the channel estimation for different emerging techniques that are capable of obtaining a better performance with a lower number of operations, suitable for low complexity devices and for URLLC. Firstly, we proposed new pilot sequences for FBMC-OQAM enabling the use of a simple averaging process in order to obtain the CSI. We show that our technique outperforms the existing ones in terms of complexity and performance. Secondly, we propose an alternative low-complexity way of computing the precoding/postcoding equalizer under the scenario of massive MIMO, keeping the quality of the estimator. Finally, we propose a new channel estimation technique for massive MIMO for mm-Wave, capable of adapting to very variable scenarios in terms of SNR and outperforming the existing techniques. We provide some analysis of the mean squared error (MSE) and complexity of each proposed technique. Furthermore, some numerical results are given in order to provide a better understanding of the problem and solutions.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Antonia María Tulino.- Secretario: Máximo Morales Céspedes.- Vocal: Octavia A. Dobr

White adipose tissue and circadian rhythm dysfunctions in obesity : Pathogenesis and available therapies

A combined neuroendocrine, metabolic, and chronobiological view can help to better understand the multiple and complex mechanisms involved in obesity development and maintenance, as well as to provide new effective approaches for its control and treatment. Indeed, we have currently updated data on the whole adipogenic process involved in white adipose tissue (WAT) mass expansion, namely due to a mechanism whereby WAT cells become hypertrophic, thus inducing a serious local (WAT) inflammatory condition that in turn, will impair not only the cross-talk between the hypothalamus and the WAT, but also favoring the development of deep and widespread neuroendocrine-metabolic dysfunction. Moreover, we also have revisited the circadian clock genes involved in dysfunctional WAT mass expansion and the mechanisms that may lead to obesity development, including early metabolic dysfunctions, enhanced oxidative stress and distorted energy homeostasis. The epigenetic changes of clock genes driving metabolic disease and obesity development have also been included in this review. Finally, we have also underlined the relevance of metabolic homeostasis regulation by central and peripheral organ clocks, sleep disturbances, nutrients, and feeding time, as key factors in obesity development as well as both, classical and chronotherapeutic approaches for its prevention and treatment.Centro de Endocrinología Experimental y Aplicad

The Intestinal Microbiota and Short-Chain Fatty Acids in Association with Advanced Metrics of Glycemia and Adiposity Among Young Adults with Type 1 Diabetes and Overweight or Obesity

BACKGROUND: Comanagement of glycemia and adiposity is the cornerstone of cardiometabolic risk reduction in type 1 diabetes (T1D), but targets are often not met. The intestinal microbiota and microbiota-derived short-chain fatty acids (SCFAs) influence glycemia and adiposity but have not been sufficiently investigated in longstanding T1D. OBJECTIVES: We evaluated the hypothesis that an increased abundance of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity were associated with improved glycemia but increased adiposity in young adults with longstanding T1D. METHODS: Participants provided stool samples at ≤4 time points (NCT03651622: https://clinicaltrials.gov/ct2/show/NCT03651622). Sequencing of the 16S ribosomal RNA gene measured abundances of SCFA-producing intestinal microbes. GC-MS measured total and specific SCFAs (acetate, butyrate, propionate). DXA (body fat percentage and percentage lean mass) and anthropometrics (BMI) measured adiposity. Continuous glucose monitoring [percentage of time in range (70-180 mg/dL), above range (>180 mg/dL), and below range (54-69 mg/dL)] and glycated hemoglobin (i.e., HbA1c) assessed glycemia. Adjusted and Bonferroni-corrected generalized estimating equations modeled the associations of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity with glycemia and adiposity. COVID-19 interrupted data collection, so models were repeated restricted to pre-COVID-19 visits. RESULTS: Data were available for ≤45 participants at 101 visits (including 40 participants at 54 visits pre-COVID-19). Abundance of Eubacterium hallii was associated inversely with BMI (all data). Pre-COVID-19, increased fecal propionate was associated with increased percentage of time above range and reduced percentage of time in target and below range; and abundances of 3 SCFA-producing taxa (Ruminococcus gnavus, Eubacterium ventriosum, and Lachnospira) were associated inversely with body fat percentage, of which two microbes were positively associated with percentage lean mass. Abundance of Anaerostipes was associated with reduced percentage of time in range (all data) and with increased body fat percentage and reduced percentage lean mass (pre-COVID-19). CONCLUSIONS: Unexpectedly, fecal propionate was associated with detriment to glycemia, whereas most SCFA-producing intestinal microbes were associated with benefit to adiposity. Future studies should confirm these associations and determine their potential causal linkages in T1D.This study is registered at clinical.trials.gov (NCT03651622; https://clinicaltrials.gov/ct2/show/NCT03651622)