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Mechanical perturbations applied to the arm can elicit reflexive actions. These rapid corrective responses include the stretch reflex, which consists of different components: the short-latency reflex (SLR) and the early and late long-latency reflex (LLR). In this study, we examine how different task factors dynamically influence these reflex components in the context of a specific delayed-reach paradigm. Using multiple linear regression (MLR), we analysed electromyographic (EMG) activity from seven muscles actuating the right arm to examine the effects of mechanical load, preparatory delay, perturbation and target direction, on reflex responses, as well as two-factor interactions. The MLR analysis shows that our delayed-reach tasks engaged shoulder girdle muscles in a task-dependent manner, whereas the biceps and triceps primarily acted as stabilizing muscles, with rapid responses triggered regardless of perturbation direction. Specifically, our analyses show that the earliest corrective response, the SLR, exhibited some task-dependent modulation particularly in muscles of the shoulder girdle, although background (pre-)loading decreased this modulation. The SLR was primarily influenced by the main factors Load and Perturbation, along with the interaction Load × Perturbation. Perturbations aligned with the load direction were associated with increased EMG activity across all examined muscles. While there was a small but significant effect of load during the early LLR, this effect diminished by the late LLR epoch. Task-dependent modulation was most pronounced at the late LLR epoch, suggesting greater top-down modulation of this reflex component. In particular, the late LLR was shaped by the factors Perturbation and Target, as well as the interaction Perturbation × Target. Targets and perturbations in opposite directions resulted in heightened EMG activity, and shoulder muscles exhibited stronger LLR responses for targets located farther along the muscle shortening direction. Our results complement and expand on previous findings concerning stretch reflex modulation and help guide the design of future studies.

Stretch reflex responses counteract sudden perturbations, and modulation of reflex gains can facilitate voluntary movement. Recent studies suggest movement preparation includes goal-directed tuning of muscle spindles and an equivalent modulation of both short- and long-latency stretch reflex responses (SLR and LLR), as long as the preparatory delay between ‘Cue’ and ‘Go’ exceeds 250 ms. The current study aimed to clarify the minimal preparation time required for goal-directed modulation of SLR and LLR responses and to determine how such modulation progressively evolves with extended preparation. We recorded bipolar electromyographic signals of healthy participants to assess reflex responses to mechanical perturbations induced by a robotic manipulandum in the context of a delayed-reach task. Specifically, we examined how multiple preparatory delays (250, 300, 350, 400, 450, and 500 ms) impact the goal-directed modulation of SLR and LLR responses from the loaded or unloaded pectoralis major, anterior deltoid, and posterior deltoid muscles. We found that preparatory delays of 300 ms and 350 ms are sufficient for goal-directed tuning of SLR responses in the posterior deltoid and pectoralis muscles, respectively. Our results also suggest that unloading (i.e., antagonist loading) may facilitate both the earlier emergence and more robust expression of goal-directed SLR tuning. Goal-directed tuning of LLR responses emerged as early as 250 ms of preparation, and such tuning was robust against muscle load conditions, in line with previous findings. We observed no consistent increase in SLR tuning at preparation delays that extended beyond the required minimum, whereas such enhancement was observed at the LLR epoch. These findings clarify the temporal characteristics of goal-directed stretch reflex gains, which likely emerge through the interplay of multiple feedback mechanisms.

Motor coordination relies on muscle spindles and the stretch reflexes they enable. A new study shows that spindle-resident macrophages can drive sensory signaling and muscle contraction. This implicates immune cells in a process considered the exclusive domain of neuromuscular systems.

Proprioception plays a crucial role in motor coordination and self-perception. Muscle spindles are the principal receptors for proprioception. They are believed to encode muscle stretch and signal limb position and velocity. Here, we applied percutaneous pressure to a small area of extensor muscles at the forearm while recording spindle afferent responses, skeletal muscle activity, and hand kinematics. Three levels of sustained pressure were applied on the spindle-bearing muscle when the hand was relaxed and immobile ("isometric" condition) and when the participant's hand moved rhythmically at the wrist. As hypothesized to occur due to compression of the spindle capsule, we show that muscle pressure is an "adequate" stimulus for human spindles in isometric conditions and that pressure enhances spindle responses during stretch. Interestingly, release of sustained pressure in isometric conditions lowered spindle firing below baseline rates. Our findings urge a re-evaluation of muscle proprioception in sensorimotor function and various neuromuscular pathologies.

Voluntary movements are prepared before they are executed. Preparatory activity has been observed across the CNS and recently documented in first-order neurons of the human PNS (i.e., in muscle spindles). Changes seen in sensory organs suggest that independent modulation of stretch reflex gains may represent an impor-tant component of movement preparation. The aim of the current study was to further investigate the preparatory modulation of short-latency stretch reflex responses (SLRs) and long-latency stretch reflex responses (LLRs) of the dominant upper limb of human subjects. Specifically, we investigated how different target pa-rameters (target distance and direction) affect the preparatory tuning of stretch reflex gains in the context of goal-directed reaching, and whether any such tuning depends on preparation duration and the direction of background loads. We found that target distance produced only small variations in reflex gains. In contrast, both SLR and LLR gains were strongly modulated as a function of target direction, in a manner that facili-tated the upcoming voluntary movement. This goal-directed tuning of SLR and LLR gains was present or enhanced when the preparatory delay was sufficiently long (.250 ms) and the homonymous muscle was unloaded [i.e., when a background load was first applied in the direction of homonymous muscle action (as-sistive loading)]. The results extend further support for a relatively slow-evolving process in reach preparation that functions to modulate reflexive muscle stiffness, likely via the independent control of fusimotor neurons. Such control can augment voluntary goal-directed movement and is triggered or enhanced when the homonymous muscle is unloaded.

The dynamic nature of movement and muscle activation emphasizes the importance of a sound experimental design. To ensure that an experiment determines what we intend, the design must be carefully evaluated. Before analyzing data, it is imperative to limit the number of outliers, biases, and skewness. In the present study, a simple center-out experiment was performed by 16 healthy volunteers. The experiment included three load conditions, two preparatory delays, two perturbations, and four targets placed along a diagonal path on a 2D plane. While the participants performed the tasks, the activity of seven arm muscles were monitored using surface electromyography (EMG). Principal component analysis (PCA) was used to evaluate the study design, identify muscle synergies, and assess the effects of individual quirks. With PCA, we can identify the trials that trigger stretch reflexes and pinpoint muscle synergies. The posterior deltoid, triceps long head, and brachioradialis were engaged when targets were in the direction of muscle shortening and the perturbation was applied in the opposite direction. Similarly, the pectoralis and anterior deltoid were engaged when the targets were in the direction of muscle shortening and the perturbation was applied in the opposite direction. The stretch reflexes were not triggered when the perturbation brought the hand in the direction of, or into the target, except if the muscle was preloaded. The use of PCA was also proven valuable when evaluating participant performance. While individual quirks are to be expected, failure to perform trials as expected can adversely affect the study results.

Most individuals experience their dominant arm as being more dexterous than the non-dominant arm, but the neural mechanisms underlying this asymmetry in motor behaviour are unclear. Using a delayed-reach task, we have recently demonstrated strong goal-directed tuning of stretch reflex gains in the dominant upper limb of human participants. Here, we used an equivalent experimental paradigm to address the neural mechanisms that underlie the preparation for reaching movements with the non-dominant upper limb. There were consistent effects of load, preparatory delay duration and target direction on the long latency stretch reflex. However, by comparing stretch reflex responses in the non-dominant arm with those previously documented in the dominant arm, we demonstrate that goal-directed tuning of short and long latency stretch reflexes is markedly weaker in the non-dominant limb. The results indicate that the motor performance asymmetries across the two upper limbs are partly due to the more sophisticated control of reflexive stiffness in the dominant limb, likely facilitated by the superior goal-directed control of muscle spindle receptors. Our findings therefore suggest that fusimotor control may play a role in determining performance of complex motor behaviours and support existing proposals that the dominant arm is better supplied than the non-dominant arm for executing more complex tasks, such as trajectory control.

Data integration has been proven to provide valuable information. The information extracted using data integration in the form of multiblock analysis can pinpoint both common and unique trends in the different blocks. When working with small multiblock datasets the number of possible integration methods is drastically reduced. To investigate the application of multiblock analysis in cases where one has a few number of samples and a lack of statistical power, we studied a small metabolomic multiblock dataset containing six blocks (i.e., tissue types), only including common metabolites. We used a single model multiblock analysis method called the joint and unique multiblock analysis (JUMBA) and compared it to a commonly used method, concatenated principal component analysis (PCA). These methods were used to detect trends in the dataset and identify underlying factors responsible for metabolic variations. Using JUMBA, we were able to interpret the extracted components and link them to relevant biological properties. JUMBA shows how the observations are related to one another, the stability of these relationships, and to what extent each of the blocks contribute to the components. These results indicate that multiblock methods can be useful even with a small number of samples

Multi-tissue metabolomics involves characterisation of the metabolome of several tissue types. The metabolome consists of small chemical entities of low molecular weight called metabolites, which are constantly produced and interchanged through a vast variety of biochemical reactions occurring throughout living organisms. Metabolome alterations can be attributed to genetics, environment, and diseases. We used gas chromatography timeof-flight mass spectrometry (GC TOF-MS) to characterise the metabolome of mouse organ samples: gut, kidney, liver, muscle, pancreas and plasma. Samples were obtained from wild-type mice and mice carrying a mutation in the hepatocyte nuclear factor 1b (HNF1b) gene, referred to as MODY5/RCAD (for maturity onset diabetes of the young 5/renal cysts and diabetes syndrome) mice. MODY is a class of hereditary diabetes mellitus, and MODY5 is caused by mutations in HNF1B, resulting in a wide range of manifestations, including renal diseases, kidney and genitourinary malformation, and elevation of liver enzymes. Today, MODY5 in humans is diagnosed using genetic tests, and varying referral rates and manifestations have resulted in misdiagnosis. Our main focus was therefore to increase understanding of the metabolism associated with MODY5/RCAD by studying the metabolic profiles of individual organs and plasma (Paper I) from MODY5/RCAD mutant and wildtype mice. The mouse model displayed an overall metabolic pattern consistent with the presumed outcome of the mutation in humans, making the MODY5/RCAD model suitable for studies of HNF1B-associated diseases. An understanding of metabolite origin would be beneficial for understanding the plasma profile associated with MODY5/RCAD. We used hierarchical modelling to provide an understanding of metabolite origin by detecting how metabolites from the organs contributed to the plasma metabolic profile (Paper II). Both specific and overall organ metabolite contributions to the plasma metabolic profile were studied. Further exploration of the dataset involved study of its innate variation using joint and unique multiblock analysis (JUMBA; Paper III). In addition, we explored the effects of improper sample handling for metabolomic multi-tissue data, and we studied the similarities and differences in the responses to thawing between organ tissues (Paper IV) and plasma samples (Paper V), thus identifying metabolic profiles that could indicate compromised samples. These profiles could be beneficial for large-scale collaborations that involve sample exposure to unsuitable conditions. Altogether, we have contributed to an increased understanding of the MODY5/RCAD multi-tissue metabolomic dataset and worked up protocols and strategies for how small datasets should be handled.

Metabolomik är identifieringen och statistiska utvärderingen av halten av metaboliter i en mängd prover. Metaboliter är små kemiska strukturer som produceras av alla reaktioner som pågår i organismer. Genom att tolka halten av metaboliter får man en uppfattning om organismens status, vid provtagningstillfället. Den relativa mängden av metaboliter i ett prov kan identifieras genom olika metoder. Till dessa identifieringsmetoder räknas exempelvis kärnmagnetisk resonans (eng. Nuclear Magnetic Resonance (NMR)) och masspektrometri-plattformar så som gaskromatografi (eng. Gas Chromatography Mass Spectrometry (GC-MS)) och vätskekromatografi (eng. Liquid Chromatography Mass Spectrometry (LC-MS)). Valet av identifieringsplattform baseras på vad studien kräver.

Metabolomikstudier skiljer sig från sina föregångare. De tidigare studierna gick ut på att mäta en eller ett par variabler med hög precision. I metabolomikstudier hittas hundratals till tusentals potentiella metaboliter i varje prov. Därtill kan dess dataset innehålla en hel del brus. Metoder i klassiska, univariata, statistiken togs fram för att tillämpas på de typer av experiment där man mäter ett fåtal variabler, med hög precision. Metabolomikdata är inte av denna karaktär, utan består av många variabler (pikar/metaboliter) och färre observationer (försöksdjur/patienter). Med hjälp av multivariat dataanalys fokuserar vi på storleken hos olika variabler och deras variation för att identifiera metabolitmönster. För att finna dessa mönster används multivariata metoder som principalkomponentanalys (eng. Principal Component Analysis (PCA)) och diskriminantanalys (eng. (Orthogonal) Projections to Latent Structures Discriminant Analysis ((O)PLS-DA), där alla variabler analyseras simultant. De univariata metoderna används sedan som ett komplement till de multivariata metoderna i utvärderingen av metabolomikdata.

I denna avhandling har arbete i huvudsak kretsat kring Maturity Onset Diabetes of the Young (MODY). MODY utgör en grupp ärftliga diabetestyper som orsakas av mutation i en enda gen som leder till att individen får en rubbad insulinproduktion och diabetesliknande symptom. Patienter med MODY blir ofta missdiagnostiserade med diagnosen Diabetes Typ 1 (DT1) eller Diabetes Typ 2 (DT2). De flesta MODY patienter har en underproduktion av insulin, men det finns ingen insulinresistens som vid DT2. Behandlingen med insulin eller tabletter leder då till svår hypoglykemi (sockerkänning). Vi studerade MODY5, vilken orsakas av en mutation i genen som kodar för transkriptionsfaktorn Hnf1b. MODY5 (eller RCAD (Renal Cysts And Diabetes syndrome)) misstänks då patienten har en DT1 eller DT2 diagnos samt njurpåverkan. Idag diagnosticeras MODY5 genom genetiska tester, dock är dessa dyra och diagnosen relativt okänd bland kliniker. Genom att öka förståelsen för sjukdomen så finns förutsättningar för att förbättra både behandling och diagnostisering.

Proverna som analyserades i denna avhandling kom från möss av vildtyp samt möss med en mutation som gav ett MODY5-liknande tillstånd. Alla möss föddes upp i Paris, Frankrike (Cereghini et al.). Då mössen var åtta månader placerades de i varsin metabol bur och övervakades noggrant i fem dagar. Såväl mat- och vattenintag som mängden urin- och avförings samt blodsocker och kroppsvikt mättes dagligen och utgör metadata. På den femte dagen offrades mössen och deras lever, muskler, njurar, bukspottkörtel och magtarmsystem samt blodplasma placerades i -80 °C frysar. Dessa skickades i två försändelser till Umeå för analys, där proverna i den ena nådde Umeå tinade.

I Paper I fastställde vi de metabola profilerna för sjukdomstillståndet (MODY5/RCAD), i var och en av de undersökta organen och plasma. MODY5/RCAD mössen uppvisade tecken på nedsatt njurfunktion och förändrad fettsyra och lipidmetabolism i organvävnaderna. Vi fann även att tarmarna påverkats mindre av mutationen, jämfört med hur det såg ut för de övriga organen och plasma. Detta kan ha att göra med att Hnf1b är viktig vid bildandet av bukspottkörtel, lever och njurar, i det unga musembryot. Varför musklerna skulle vara mer påverkade än tarmen krävs det vidare studier för att fastställa.

I Paper II fokuserade vi på hur de olika organen bidrar till metaboliterna i blodplasma och undersökte vilka metaboliter som varje organ bidrar med till plasma. Målet med denna studie var att undersöka hur hierarkisk modellering kan användas för att identifiera detta bidrag. Vi visade att alla undersökta organ bidrog till metabolitnivåerna hos blodplasma, men att det var mag-tarmsystemet som hade största bidraget. Den hierarkiska modellen kunde även vis på de organspecifika metabolitbidraget till blodplasma. Då de identifierade flödena överensstämde med vad vi kunde förvänta oss, baserat på rådande forskning, skulle denna strategi kunna användas för att studera flödet av okända metaboliter.

Paper III behandlar hur man kan utföra dataintegrering av ett litet dataset. Genom att integrerar data från olika block (i detta fall representerade varje vävnadstyp ett block) kunde vi identifiera gemensamma mönster, gemensam variation. Den integrationsmetod vi använde var JUMBA (Joint and Unique MultiBlock Analysis) som kan identifiera både global variation (som återfinns i alla block), lokal variation (som återfinns i några av blocken) och unik variation (endast återfunnen i ett block). JUMBA extraherade två globala komponenter som vi kunde tolka som en annorlunda aminosyraprofil och fettsyraprofil hos en av mössen, samt att vissa skillnader berodde på mössens storlek. JUMBA fann även upp de två genotyperna, i alla block utom mag-tarmsystemet (alltså i en lokal komponent) vilket överensstämmer med fynden i Paper I. I en andra lokal komponent fann JUMBA hur de olika mössen befann sig i tre olika stadier av energimetabolism. Detta indikerar att JUMBA lämpar sig för att få fram information, även i fall med få prover.

I Paper IV undersökte vi hur de olika vävnadstyperna reagerat på upptining. De metabola profilerna hos prover som tinat under transporten jämfördes mot sådana som behandlats enligt standardprotokoll (SOP). Genom att identifiera metaboliter som är specifika för felbehandlade, tinade prover fann vi ett metabolitmönster som ska ses som alarmerande. De olika organproverna reagerade likartat på att ha tinat under transporten, med proteindegradering och cellsönderfall. Om denna typ av mönster observeras måste provens kvalité granskas. I en andra studie av tinade prover (Paper V) jämförde vi dessa resultat med de tinade plasmaproven och fann att organproverna var känsligare för upptining. Dock uppstod förändringar även i plasmaproverna.

Sammanfattningsvis har denna avhandling bidragit till en ökad förståelse för detta multivävnads dataset och upparbetat protokoll för hur små dataset (där små dataset avser sådana med färre än femton observationer per grupp) ska hanteras. Vi har bedömt hur väl MODY5/RCAD musmodellen skulle fungera som modell och dess potential i pre-kliniska studier av HNF1 B-associerade sjukdomar. Vi har studerat hur olika organ bidrar till de metabolitnivåer som återfinns i blodplasma. Vikten av att prover hanteras korrekt och på samma sätt samt vikten av randomisering har också diskuterats. Dessutom har vi diskuterat olika multivariata dataanalysmetoder och betydelsen av de metabola variationer vi identifierat.

Mycket har hänt inom metabolomik under mina år som doktorand, det är fortfarande ett relativt ungt fält men med mycket tydligare riktlinjer. Stora insatser har lagts på att standardisera namngivningen av metaboliter och hanteringen av prover. Mängden metaboliter som identifieras har ökat enormt och så även precisionen med vilken de mäts. Väl upparbetade standardprotokoll finns och kunskapen om olika metaboliter ökar för var dag som går. Fältet som sådant visar enorm potential vad gäller diagnostisering och monitorering av sjukdomar samt identifiering av nya behandlingsmål. Jag ser framemot att följa dess utveckling vidare.

The aim of this study was to evaluate how the cytokine profiles differed between autoantibody based subgroups of systemic lupus erythematosus (SLE). SLE is a systemic autoimmune disease, characterized by periods of flares (active disease) and remission (inactive disease). The disease can affect many organ systems, e.g., skin, joints, kidneys, heart, and the central nervous system (CNS). SLE patients often have an overproduction of cytokines, e.g., interferons, chemokines, and interleukins. The high cytokine levels are part of the systemic inflammation, which can lead to tissue injury. In the present study, SLE patients were divided into five groups based on their autoantibody profiles. We thus defined these five groups: ANA negative, antiphospholipid (aPL) positive, anti-Sm/anti-RNP positive, Sjögren’s syndrome (SS) antigen A and B positive, and patients positive for more than one type of autoantibodies (other SLE). Cytokines were measured using Mesoscale Discovery (MSD) multiplex analysis. On the basis of the cytokine data, ANA negative patients were the most deviating subgroup, with lower levels of interferon (IFN)-γ, tumor necrosis factor (TNF)-α, interleukin (IL)-12/IL-23p40, and interferon gamma-induced protein (IP)-10. Despite low cytokine levels in the ANA negative group, autoantibody profiles did not discriminate between different cytokine patterns.