Explorative Analysis and Data Mining in Big Neural Data

Most motor actions are carried out by many neurons acting together in different areas of the brain. Recently, techniques have been developed and increasingly used that allow simultaneous recordings of the activity from a large number of neurons over time ranges as long as several weeks. At Neuronano Research Center (NRC) at Lund University, neural activity in rodents has been recorded using chronically implanted 128-channel electrodes. The targets are within areas that play a prominent role in the planning, monitoring and execution of movements and, consequently, are strongly affected by motor diseases such as Parkinson’s disease. The experiments conducted at NRC naturally produces a large amount of neural data. This master thesis work aims to perform feature extraction from that data, i.e., find a way to mathematically describe the disease states of the rodents without a priori knowledge of the states. This is done by extracting features from the recordings, whose values later are used to analyse and cluster the data. The results show that a clear majority of the neurons exhibit a significant difference in feature values between the disease states. This means that it is possible to mathematically describe the different disease states. Moreover, the results show that different neurons behave differently: Some, e.g., exhibit increased activity going from one state to another, while others exhibit decreased activity. Adding to this, some does not exhibit any change while others exhibit a significant change. That it is possible to mathematically describe the different disease states, with a timescale of hours, indicate that the same may be possible for states with smaller timescales. These states, with a smaller timescale, do not have to be connected to Parkinson’s disease but could rather be normal, healthy states such as locomotion or reaching.Parkinson’s – a mathematical description In search for answers to how the brains of Parkinson patients function there are not many tools available. One of them proves to be mathematics. Another is rodent experiments, which play an important and necessary role in the process of finding new treatments for the disease. Research indicate that, in rodents, it is possible to distinguish between different states of health and disease by using mathematical analysis. This can be done by analysing the brain signals of the animal, and this without knowing what state the animal is in at that time. It seems possible to use mathematics to describe different states of health and disease, opening up new possibilities on the road to finding new treatments. But, how does this actually work? Parkinson’s disease is the second most common degenerative disease. It damages the brain with consequences such as impaired movements, tremors at rest, dementia and, finally, 10 to 20 years later, death. The knowledge of exactly how the area of the brain affected by Parkinson’s works is unfortunately still limited. Better knowledge could lead to the development of new treatments, hopefully with less side effects than those currently used. The brain is the part of our body that controls our thoughts, feelings and actions. It interprets, helping us to make sense of the world, and controls actions such as breathing, talking and moving (to mention very few). Our actions, including movements, are controlled by the use of nerve cells, called neurons, connected to each other in a complicated network. The neurons use this network to communicate with each other by sending and receiving electrical signals: action potentials. At Neuronano Research Center (NRC), Lund University, a group of scientists has found a way to perform the very challenging task of recording the signals from a lot of these tiny neurons. The brain signals recorded are from rats and, specifically, from neurons in an area of their brain that controls movements. The reason that this area has been chosen is that it is strongly affected by diseases that impair our movements, such as Parkinson’s disease. The rats used in the experiments at NRC have received drug injections infecting half of their brains with Parkinson’s disease. In this way, the healthy half of the brain can be used as a reference when analysing what happens in the other, diseased half. During the experiments, action potentials from neurons in both the healthy and diseased part of the brain are recorded and saved, resulting in a very large dataset. The amount of action potentials, as well as the pattern that they are fired in affects the message being sent. Let us look at a simple example: A sequence of action potentials, sent from a neuron, can be represented by ones and zeros. A one is an action potential and a zero means that nothing happened at that time: 1 1 0 1 1 0 1 1 0 1 1 0 0 1 1 0 0 0 1 0 1 0 0 1 The first sequence consists of two ones followed by a zero whereas the second does not follow any obvious pattern. Also, the first one has more action potentials (eight) than the other has (five). These properties, among many others, can easily be expressed mathematically. It has been found that the sequences of action potentials change when the behaviour changes: The meaning of a certain sequence from a certain neuron is not yet known, but maybe it will be in the future! But, the fact that sequences change when the behaviour of the animal changes is a strong motivation to continue the search: Answers to how our brains function and new treatments for diseases can be uncovered by means of mathematics

Deglaciation of the highest mountains in Scandinavia at the Younger Dryas-Holocene transition: evidence from surface exposure-age dating of ice-marginal moraines

Surface exposure-age dating was applied to rock surfaces associated with ice-marginal moraines at elevations of ~1520–1780 m a.s.l. on the slopes of Galdhøpiggen and Glittertinden, the two highest mountains in Scandinavia located in the Jotunheimen mountains of central southern Norway. This is important for understanding the pattern and timing of wastage of the Scandinavian Ice Sheet at the Younger Dryas-Holocene transition. Cosmogenic exposure dating (here 10Be dating) of boulders from the moraine ridges yielded overall mean ages (corrected for glacio-isostatic uplift, surface erosion and snow shielding) of ~11.6 ka from Galdhøpiggen and ~11.2 ka from Glittertinden. Similar 10Be ages were also obtained from additionally collected proximal and distal erratic boulders and bedrock samples.These enabled age calibration of Schmidt-hammer R-values and independent Schmidt-hammer exposure-age dating (SHD) of the moraine ridges, which yielded comparable mean SHD ages of ~10.8 ka and ~10.6 ka from the Galdhøpiggen and Glittertinden sites, respectively. Taking account of the age-resolution and other limitations of both dating techniques, the results suggest that the two sets of moraines have approximately the same age but that neither technique can distinguish unambiguously between moraine formation in the late Younger Dryas or Early Holocene. Together with features of moraine-ridge morphology and estimates of equilibrium-line altitude depression (ΔELA) of ~360–575 m (corrected for land uplift), the results imply moraine formation during short-lived re-advances of active glaciers, at least the lower reaches of which were warm-based. It is concluded that the local glaciers remained active and advanced during deglaciation either very late in the Younger Dryas or very early in the Holocene, possibly in response to the Preboreal Oscillation at ~11.4 ka. The study supports the concept of a thin Younger Dryas Ice Sheet and places time constraints on the timing of final deglaciation in southern Norway

Psoriatic arthritis is associated with adverse body composition predictive of greater coronary heart disease and type 2 diabetes propensity – a cross-sectional study

Objectives: To compare body composition in PsA with metabolic disease free (MDF) controls and type 2 diabetes and assess body-composition predicted propensity for cardiometabolic disease. Methods: Detailed MRI body composition profiles of 26 PsA participants from the IMAPA study were compared with 130 age, sex and BMI-matched MDF controls and 454 individuals with type 2 diabetes from UK Biobank. The body-composition predicted propensity for coronary heart disease (CHD) and type 2 diabetes was compared between PsA and matched MDF controls. Results: PsA participants had a significantly greater visceral adipose tissue (VAT) volume [mean 5.89 l (S.D. 2.10 l)] compared with matched-MDF controls [mean 4.34 l (S.D. 1.83 l)] (P <0.001) and liver fat percentage [median 8.88% (interquartile range 4.42–13.18%)] compared with MDF controls [3.29% (1.98–7.25%)] (P <0.001). These differences remained significant after adjustment for age, sex and BMI. There were no statistically significant differences in VAT, liver fat or muscle fat infiltration (MFI) between PsA and type 2 diabetes. PsA participants had a lower thigh muscle volume than MDF controls and those with type 2 diabetes. Body composition-predicted propensity for CHD and type 2 diabetes was 1.27 and 1.83 times higher, respectively, for PsA compared with matched-MDF controls. Conclusion: Individuals with PsA have an adverse body composition phenotype with greater visceral and ectopic liver fat and lower thigh muscle volume than matched MDF controls. Body fat distribution in PsA is more in keeping with the pattern observed in type 2 diabetes and is associated with greater propensity to cardiometabolic disease. These data support the need for greater emphasis on weight loss in PsA management to lessen CHD and type 2 diabetes risk

Associations between abdominal adipose tissue, reproductive span, and brain characteristics in post-menopausal women

The menopause transition involves changes in oestrogens and adipose tissue distribution, which may influence female brain health post-menopause. Although increased central fat accumulation is linked to risk of cardiometabolic diseases, adipose tissue also serves as the primary biosynthesis site of oestrogens post-menopause. It is unclear whether different types of adipose tissue play diverging roles in female brain health post-menopause, and whether this depends on lifetime oestrogen exposure, which can have lasting effects on the brain and body even after menopause. Using the UK Biobank sample, we investigated associations between brain characteristics and visceral adipose tissue (VAT) and abdominal subcutaneous adipose tissue (ASAT) in 10,251 post-menopausal females, and assessed whether the relationships varied depending on length of reproductive span (age at menarche to age at menopause). To parse the effects of common genetic variation, we computed polygenic scores for reproductive span. The results showed that higher VAT and ASAT were both associated with higher grey and white matter brain age, and greater white matter hyperintensity load. The associations varied positively with reproductive span, indicating more prominent associations between adipose tissue and brain measures in females with a longer reproductive span. The effects were in general small, but could not be fully explained by genetic variation or relevant confounders. Our findings indicate that associations between abdominal adipose tissue and brain health post-menopause may partly depend on individual differences in cumulative oestrogen exposure during reproductive years, emphasising the complexity of neural and endocrine ageing processes in females

Dissecting unique and common variance across body and brain health indicators using age prediction

Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter‐individual heterogeneity in the multisystem ageing process. Using machine‐learning regression models on the UK Biobank data set (N = 32,593, age range 44.6–82.3, mean age 64.1 years), we first estimated tissue‐specific brain age for white and gray matter based on diffusion and T1‐weighted magnetic resonance imaging (MRI) data, respectively. Next, bodily health traits, including cardiometabolic, anthropometric, and body composition measures of adipose and muscle tissue from bioimpedance and body MRI, were combined to predict ‘body age’. The results showed that the body age model demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. The correlation between body age and brain age predictions was 0.62 for the T1 and 0.64 for the diffusion‐based model, indicating a degree of unique variance in brain and bodily ageing processes. Bayesian multilevel modelling carried out to quantify the associations between health traits and predicted age discrepancies showed that higher systolic blood pressure and higher muscle‐fat infiltration were related to older‐appearing body age compared to brain age. Conversely, higher hand‐grip strength and muscle volume were related to a younger‐appearing body age. Our findings corroborate the common notion of a close connection between somatic and brain health. However, they also suggest that health traits may differentially influence age predictions beyond what is captured by the brain imaging data, potentially contributing to heterogeneous ageing rates across biological systems and individuals

A rock-surface microweathering index from Schmidt hammer R-values and its preliminary application to some common rock types in southern Norway

An index of the degree of rock-surface microweathering based on Schmidt hammer R-values is developed for use in the field without laboratory testing. A series of indices - I2 to In, where n is the number of successive blows with the hammer - is first proposed based on the assumption that the R-values derived from successive impacts on the same spot on a weathered rock surface converge on the value characteristic of an unweathered surface of the same lithology. Of these indices, the I5 index, which measures the difference between the mean R-value derived from first and fifth impacts as a proportion of the mean R-value from the fifth impact, is regarded as optimal: use of fewer impacts (e.g. in an I2 index) underestimates the degree of weathering whereas use of more impacts (e.g. in an I10 index) makes little difference and is therefore inefficient and may also induce an artificial weakening of the rock. Field tests of these indices on weathered glacially-scoured bedrock outcrops of nine common metamorphic and igneous rock types from southern Norway show, however, that even after ten impacts, successive R-values fail to approach the values characteristic of unweathered rock surfaces (e.g. bedrock from glacier forelands and road cuttings). An improved *I5 index is therefore preferred, in which the estimated true R-value of an unweathered rock surface is substituted. Weathered rock surfaces exposed to the atmosphere for ~10,000 years in southern Norway exhibit *I5 indices of 36-57%, values that reflect a similarly high degree of weathering irrespective of the rock type

Adverse Muscle Composition : Revisiting Sarcopenia in General Population and Liver Disease using Magnetic Resonance Imaging

Sarcopenia - from the Greek words 'sarx' (flesh) and 'penia' (loss) - was, when coined in 1989, a term denoting the decline in muscle mass and strength that occurs with aging. Such definition implies everyone suffers from sarcopenia to varying degrees, which naturally makes studying sarcopenia challenging. Early (practical) definitions of sarcopenia focused on identification of low muscle mass, while later definitions also include criteria of low muscle strength. Use of such definitions to study sarcopenia has shown that wasting is intensified in those suffering from metabolic diseases, and even more rapid in end-stage diseases. Although it is unknown whether sarcopenia accelerate disease or the other way around, detection of sarcopenia concurrent with other diseases clearly identifies a vulnerable subgroup of patients who may need more extensive care. In severe stages of liver disease, poor muscle health has been linked to higher morbidity and mortality, and may affect the outcome of liver transplantation. Sarcopenia is therefore recognized as an important factor that should affect both clinical decision-making and intervention in patients being evaluated for liver transplantation. However, sarcopenia is poorly understood (and commonly overlooked) in earlier stages of disease, where the potential of preventative care is greater. One challenge has been the prevalence of obesity in diseases that may precede more advanced disease, such as non-alcoholic fatty liver disease (NAFLD). Due to their larger body size, individuals with obesity need more muscle mass to maintain mobility function. Therefore, the threshold for what is considered ‘low muscle mass’ needs to be higher, or somehow adjusted for body size. This thesis started by applying the European definition of sarcopenia in 10,000 individuals aged 44-78 years volunteering for the UK Biobank imaging study. It was identified that current body size adjustments used to detect 'low muscle mass' were ineffective. The consequence of this was underdiagnosis of sarcopenia in individuals with overweight and obesity. Therefore, a more personalized muscle volume assessment, that was independent of body size, was developed with the aim to describe how much an individual is deviating from what is expected and address whether they have an 'adequate' amount of muscle volume - muscle volume z-score. Muscle volume was measured using magnetic resonance imaging and from the same images, muscle fat infiltration (indicating muscle quality) was also quantified. The first results indicated that muscle volume z-score and muscle fat infiltration were independently associated with mobility function and hospitalization, and that a combination of the two may identify the most vulnerable individuals. Therefore, thresholds were suggested to identify an adverse muscle composition (low muscle volume z-score combined with high muscle fat infiltration). Following studies investigated associations of adverse muscle composition with metabolic diseases, mobility function, and mortality in general population and NAFLD. Overall, the studies showed that adverse muscle composition was associated with increased morbidity and mortality independent of mobility function, and indicated that muscle composition assessment could provide clinically relevant information that may be useful in risk-stratification of heterogeneous disease populations like NAFLD.Today, the relevance of adverse muscle composition and potential clinical use cases are evaluated in the liver transplant setting through both European and American clinical studies.Sarkopeni - från grekiskans 'sarx' (kött) och 'penia' (förlust) - syftade, när uttrycket myntades 1989, till förlust av muskelmassa och funktion i samband med åldrande. En sådan definition är inte speciellt praktiskt för studerandet av sarkopeni då den innebär att alla har (till olika grad) sarkopeni. Tidiga (praktiskt tillämpbara) definitioner av sarkopeni fokuserade på identifiering av låg muskelmassa men senare inkluderar även krav på låg muskelstyrka. Studier av sarkopeni som använt dessa definitioner har visat att muskelförtvining är intensifierad inom metabola sjukdomar och än mer aggressiv vid terminal sjukdom. Trots detta är det fortfarande okänt om sarkopeni accelererar utvecklingen av andra sjukdomar eller tvärt om. Det är dock tydligt att individer med sarkopeni och samsjuklighet är mer sårbara än andra och har större vårdbehov. Hos individer med svår leversjukdom har nedsatt muskelhälsa bland annat kopplats till högre sjuklighet och dödlighet samt visats påverka resultatet efter levertransplantation. Därför anses sarkopeni vara en viktig faktor som bör övervägas vid patientbeslut och interventioner för patienter som utvärderas för levertransplantation. Vid tidigare faser av leversjukdom är förståelsen för sarkopeni mer begränsad och tillståndet är sällan uppmärksammat inom vården. En utmaning är den höga förekomsten av obesitas inom sjukdomar (så som fettlever eller diabetes) som kan föregå mer avancerad sjukdom. På grund av större kroppsstorlek, behöver individer med obesitas mer muskelmassa för att bibehålla rörlighet. Därför behövs en högre tröskel för vad som anses vara 'låg muskelmassa', eller alternativt ett mått på muskelmassa som är korrigerat för kroppsstorlek. Den här avhandlingen börjar med att tillämpa den europeiska definitionen av sarkopeni på 10,000 frivilliga deltagare från UK Biobank med åldern 44-78. Det visades att dagens metoder för korrigering av kroppsstorlek inte fungerade, vilket ledde till underdiagnostisering av sarkopeni hos individer med övervikt och obesitas. Därför utvecklades ett mer individualiserat mått på muskelvolym, vilket kunde användas oberoende av kroppsstorlek. Syftet var att beskriva hur mycket någon avviker från förväntad muskelvolym och indikera huruvida de har 'tillräcklig' muskelvolym - ett z-score för muskelvolym. Muskelvolymen mättes med hjälp av magnetresonanstomografi (MR) och från samma bilder mättes även fettinfiltration (vilket indikerar muskelkvalitet). De första resultaten indikerade att både z-score och fettinfiltration var kopplade till funktion och hospitalisering, samt att de mest sårbara individerna skulle kunna identifieras genom att kombinera zscore och fettinfiltration. Därför föreslogs trösklar för att identifiera vad som på engelska kallades 'adverse muscle composition' - en 'ogynnsam muskelsammansättning' - definierad av låg z-score kombinerat med hög fettinfiltration. Följande studier undersökte hur adverse muscle composition var kopplat till metabola sjukdomar, muskelfunktion och dödlighet hos studiedeltagare i UK Biobank samt bland dem med fettleversjukdom. Studierna visade att adverse muscle composition var kopplad till ökad sjuklighet och dödlighet oberoende av muskelfunktion och indikerade att kunskap om muskelsammansättning skulle kunna användas för att identifiera hög- respektive lågriskpatienter inom heterogena sjukdomar så som fettlever. Idag utvärderas metoden för att beskriva muskelsammansättning och diagnostik av adverse muscle composition för användning inom vården vid behandling av leversvikt och inför levertransplantation genom kliniska studier både i Europa och Nordamerika

Reply to: "Rationale of adding muscle volume to muscle fat infiltration in the definition of an adverse muscle composition is unclear"

n/aFunding Agencies|Pfizer Inc.Pfizer</p

Adverse muscle composition is linked to poor functional performance and metabolic comorbidities in NAFLD

Background &amp; Aims: Sarcopenia and frailty are recognised as important factors in later stages of liver disease. However, theirrole in non-alcoholic fatty liver disease (NAFLD) is not yet fully understood. In this study we investigate the associations ofMRI-measured adverse muscle composition (AMC: low muscle volume and high muscle fat) with poor function, sarcopenia,and metabolic comorbidity within NAFLD in the large UK Biobank imaging study. Methods: A total of 9,545 participants were included. Liver fat, fat-tissue free muscle volume, and muscle fat infiltration werequantified using a rapid MRI protocol and automated image analysis (AMRA® Researcher). For each participant, a personalisedmuscle volume z-score (sex- and body size-specific) was calculated and combined with muscle fat infiltration for AMC detection. The following outcomes were investigated: functional performance (hand grip strength, walking pace, stairclimbing, falls) and metabolic comorbidities (coronary heart disease, type 2 diabetes). Sarcopenia was detected by combiningMRI thresholds for low muscle quantity and low hand grip strength according to the European working group definition. Results: The prevalence of sarcopenia in NAFLD (1.6%) was significantly lower (p &lt;0.05) compared with controls without fattyliver (3.4%), whereas the prevalence of poor function and metabolic comorbidity was similar or higher. Of the 1,204 participants with NAFLD, 169 (14%) had AMC and showed 1.7–2.4× higher prevalence of poor function (all p &lt;0.05) as well as 2.1×and 3.3× higher prevalence of type 2 diabetes and coronary heart disease (p &lt;0.001), respectively, compared with thosewithout AMC. Conclusions: AMC is a prevalent and highly vulnerable NAFLD phenotype displaying poor function and high prevalence ofmetabolic comorbidity. Sarcopenia guidelines can be strengthened by including cut-offs for muscle fat, enabling AMCdetection.Funding agency: Pfizer Inc.</p

On the Definition of Sarcopenia in the Presence of Aging and Obesity-Initial Results from UK Biobank

BACKGROUND: Current consensus is to combine a functional measure with muscle quantity to assess/confirm sarcopenia. However, the proper body size adjustment for muscle quantity is debated and sarcopenia in obesity is not well described. Further, functional measures are not muscle-specific or sensitive to etiology, and can be confounded by, for example, fitness/pain. For effective detection/treatment/follow-up, muscle-specific biomarkers linked to function are needed. METHODS: Nine thousand six hundred and fifteen participants were included and current sarcopenia thresholds (EWGSOP2: DXA, hand grip strength) applied to investigate prevalence. Fat-tissue free muscle volume (FFMV) and muscle fat infiltration (MFI) were quantified through magnetic resonance imaging (MRI) and sex-and-body mass index (BMI)-matched virtual control groups (VCGs) were used to extract each participant's FFMV/height2 z-score (FFMVVCG). The value of combining FFMVVCG and MFI was investigated through hospital nights, hand grip strength, stair climbing, walking pace, and falls. RESULTS: Current thresholds showed decreased sarcopenia prevalence with increased BMI (underweight 8.5%/normal weight 4.3%/overweight 1.1%/obesity 0.1%). Contrary, the prevalence of low function increased with increasing BMI. Previously proposed body size adjustments (division by height2/weight/BMI) introduced body size correlations of larger/similar magnitude than before. VCG adjustment achieved normalization and strengthened associations with hospitalization/function. Hospital nights, low hand grip strength, slow walking pace, and no stair climbing were positively associated with MFI (p &lt; .05) and negatively associated with FFMVVCG (p &lt; .01). Only MFI was associated with falls (p &lt; .01). FFMVVCG and MFI combined resulted in highest diagnostic performance detecting low function. CONCLUSIONS: VCG-adjusted FFMV enables proper sarcopenia assessment across BMI classes and strengthened the link to function. MFI and FFMV combined provides a more complete, muscle-specific description linked to function enabling objective sarcopenia detection.Funding agencies: Medical Research CouncilMedical Research Council UK (MRC) [MC_PC_17228, MC_QA137853] Funding Source: Medline</p